--------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\smncr\OneDrive - Università Commerciale Luigi Bocconi\VAIA\JOP Dataverse\Dataverse\Stata_log.log
  log type:  text
 opened on:   6 Jun 2024, 09:42:33

. 
. do "replication.do"

. ***************************************************************
. * This script reproduces all Stata results
. * Run this script before replication.R
. * Before running, set working directory to the project's folder
. * Results are based on Stata 18
. ***************************************************************
. 
. * set Stata version
. *version 18
. 
. * install additional packages if needed
. *ssc install estout
. 
. ****************************************************************
. * Coefficient Plots of First Difference Estimates
. ****************************************************************
. 
. * Incumbent
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22)) | (party == "SVP" & cod_prov == 21)
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. 
. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. gen diffshare=party_share-l5.party_s
(650 missing values generated)

. 
. reg diffsh i.damage_binary i.cod_pro if anno == 2019, cluster(SLL)

Linear regression                               Number of obs     =        650
                                                F(6, 51)          =    1361.20
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8988
                                                Root MSE          =     .05444

                                 (Std. err. adjusted for 52 clusters in SLL_2011)
---------------------------------------------------------------------------------
                |               Robust
      diffshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
1.damage_binary |   .0300795   .0075165     4.00   0.000     .0149895    .0451695
                |
       cod_prov |
            22  |   .3805224   .0144046    26.42   0.000     .3516041    .4094408
            24  |    .427432   .0070522    60.61   0.000     .4132742    .4415898
            25  |   .4109181   .0108336    37.93   0.000     .3891687    .4326676
            30  |   .4345253   .0081384    53.39   0.000     .4181869    .4508637
            93  |   .4254721   .0082313    51.69   0.000     .4089471    .4419971
                |
          _cons |  -.0525566   .0034284   -15.33   0.000    -.0594394   -.0456737
---------------------------------------------------------------------------------

. reg diffsh i.damage_binary i.cod_pro if anno == 2014, cluster(SLL)

Linear regression                               Number of obs     =        642
                                                F(6, 51)          =      74.45
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5649
                                                Root MSE          =     .04188

                                 (Std. err. adjusted for 52 clusters in SLL_2011)
---------------------------------------------------------------------------------
                |               Robust
      diffshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
1.damage_binary |  -.0072053   .0082639    -0.87   0.387    -.0237957    .0093852
                |
       cod_prov |
            22  |  -.0502775   .0106054    -4.74   0.000    -.0715687   -.0289863
            24  |  -.1386189   .0075295   -18.41   0.000     -.153735   -.1235028
            25  |  -.1329796   .0106828   -12.45   0.000    -.1544262    -.111533
            30  |   -.052915   .0065984    -8.02   0.000    -.0661619   -.0396681
            93  |  -.0935077    .008711   -10.73   0.000    -.1109957   -.0760197
                |
          _cons |  -.0366666   .0041455    -8.84   0.000     -.044989   -.0283441
---------------------------------------------------------------------------------

. reg diffsh i.damage_binary i.cod_pro if anno == 2009, cluster(SLL)

Linear regression                               Number of obs     =        633
                                                F(6, 51)          =      25.13
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4057
                                                Root MSE          =     .03884

                                 (Std. err. adjusted for 52 clusters in SLL_2011)
---------------------------------------------------------------------------------
                |               Robust
      diffshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
1.damage_binary |   .0004801    .005903     0.08   0.935    -.0113706    .0123308
                |
       cod_prov |
            22  |   .0324548   .0076798     4.23   0.000     .0170369    .0478727
            24  |   .1006537   .0088505    11.37   0.000     .0828856    .1184218
            25  |   .0568338   .0086303     6.59   0.000     .0395076    .0741599
            30  |    .024679   .0069696     3.54   0.001     .0106869    .0386712
            93  |   .0448014     .00827     5.42   0.000     .0281985    .0614042
                |
          _cons |   .0697008   .0054974    12.68   0.000     .0586643    .0807373
---------------------------------------------------------------------------------

. 
. keep pro_com anno diffsh damage* cod_pro SLL

. 
. saveold "FD_incumbent.dta", version(12) replace
(saving in Stata 12 format, which can be read by Stata 11 or 12)
(file FD_incumbent.dta not found)
file FD_incumbent.dta saved

. 
. * Greens
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if party == "green" 
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. keep if anno == 2004 | anno == 2014 | anno == 2019
(642 observations deleted)

. 
. bys pro_com (anno): gen year = _n

. xtset pro_com year

Panel variable: pro_com (unbalanced)
 Time variable: year, 1 to 3
         Delta: 1 unit

. gen diffshare=party_share-l.party_s
(650 missing values generated)

. 
. reg diffsh i.damage_binary i.cod_pro if anno == 2019, cluster(SLL)

Linear regression                               Number of obs     =        650
                                                F(6, 51)          =      27.20
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3351
                                                Root MSE          =     .01286

                                 (Std. err. adjusted for 52 clusters in SLL_2011)
---------------------------------------------------------------------------------
                |               Robust
      diffshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
1.damage_binary |   .0006187   .0020887     0.30   0.768    -.0035746    .0048121
                |
       cod_prov |
            22  |   -.019346   .0036891    -5.24   0.000    -.0267522   -.0119399
            24  |   -.023892   .0023477   -10.18   0.000    -.0286052   -.0191789
            25  |  -.0255982   .0029876    -8.57   0.000     -.031596   -.0196004
            30  |   -.024528   .0021697   -11.30   0.000    -.0288838   -.0201722
            93  |  -.0258653   .0021789   -11.87   0.000    -.0302396    -.021491
                |
          _cons |   .0395767   .0020808    19.02   0.000     .0353993     .043754
---------------------------------------------------------------------------------

. reg diffsh i.damage_binary i.cod_pro if anno == 2014, cluster(SLL)

Linear regression                               Number of obs     =        633
                                                F(6, 51)          =      13.80
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6490
                                                Root MSE          =     .02556

                                 (Std. err. adjusted for 52 clusters in SLL_2011)
---------------------------------------------------------------------------------
                |               Robust
      diffshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
1.damage_binary |   .0017312   .0028237     0.61   0.543    -.0039376    .0074001
                |
       cod_prov |
            22  |   .0833122   .0132118     6.31   0.000     .0567885    .1098359
            24  |   .0866309    .013451     6.44   0.000     .0596269    .1136349
            25  |   .0923282   .0131998     6.99   0.000     .0658285    .1188279
            30  |   .0947572   .0133803     7.08   0.000     .0678951    .1216193
            93  |   .0934184   .0133361     7.00   0.000      .066645    .1201917
                |
          _cons |  -.1081485   .0133758    -8.09   0.000    -.1350015   -.0812955
---------------------------------------------------------------------------------

. 
. keep pro_com anno diffsh damage* cod_pro SLL

. 
. saveold "FD_greens.dta", version(12) replace
(saving in Stata 12 format, which can be read by Stata 11 or 12)
(file FD_greens.dta not found)
file FD_greens.dta saved

. 
. * M5S
. use "vaia.dta", clear
(Written by R.              )

. keep if party == "M5S" 
(60,624 observations deleted)

. keep if damaged_prov_binary == 1 
(2,336 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. keep if anno == 2014 | anno == 2019
(0 observations deleted)

. 
. xtset pro_com anno

Panel variable: pro_com (strongly balanced)
 Time variable: anno, 2014 to 2019, but with gaps
         Delta: 1 unit

. 
. gen diffshare=party_share-l5.party_s
(650 missing values generated)

. 
. reg diffsh i.damage_binary i.cod_pro if anno == 2019, cluster(SLL)

Linear regression                               Number of obs     =        650
                                                F(6, 51)          =      52.88
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4669
                                                Root MSE          =     .03234

                                 (Std. err. adjusted for 52 clusters in SLL_2011)
---------------------------------------------------------------------------------
                |               Robust
      diffshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
1.damage_binary |  -.0021519   .0052879    -0.41   0.686    -.0127678     .008464
                |
       cod_prov |
            22  |  -.0234157   .0063493    -3.69   0.001    -.0361624    -.010669
            24  |  -.0811058   .0057726   -14.05   0.000    -.0926947   -.0695169
            25  |  -.0498823   .0082619    -6.04   0.000    -.0664687   -.0332958
            30  |  -.0711965   .0060211   -11.82   0.000    -.0832843   -.0591087
            93  |  -.0738302   .0064296   -11.48   0.000    -.0867382   -.0609222
                |
          _cons |  -.0300631   .0035778    -8.40   0.000    -.0372458   -.0228804
---------------------------------------------------------------------------------

. 
. keep pro_com anno diffsh damage* cod_pro SLL

. 
. saveold "FD_M5S.dta", version(12) replace
(saving in Stata 12 format, which can be read by Stata 11 or 12)
(file FD_M5S.dta not found)
file FD_M5S.dta saved

. 
. ****************************************************************
. * Event Study Plot of TWFE, IPW-TWFE, and Placebo Estimates
. ****************************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22)) | (party == "SVP" & cod_prov == 21)
(55,979 observations deleted)

. keep if anno == 2004 | anno == 2009 | anno == 2014 | anno == 2019
(0 observations deleted)

. 
. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. 
. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. gen logalt = log(mean_altitude+1)

. 
. logit damage_binary logalt income_ind_2017 pop_tot_1jan18 forest_perc pop_dens18 foreign_share_1jan18 if anno == 2019 

Iteration 0:  Log likelihood = -363.15298  
Iteration 1:  Log likelihood = -295.65193  
Iteration 2:  Log likelihood = -274.35475  
Iteration 3:  Log likelihood = -267.76439  
Iteration 4:  Log likelihood = -267.49943  
Iteration 5:  Log likelihood = -267.49866  
Iteration 6:  Log likelihood = -267.49866  

Logistic regression                                     Number of obs =    640
                                                        LR chi2(6)    = 191.31
                                                        Prob > chi2   = 0.0000
Log likelihood = -267.49866                             Pseudo R2     = 0.2634

--------------------------------------------------------------------------------------
       damage_binary | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
---------------------+----------------------------------------------------------------
              logalt |   2.242553   .3488311     6.43   0.000     1.558857     2.92625
     income_ind_2017 |  -.0001149   .0000471    -2.44   0.015    -.0002073   -.0000226
      pop_tot_1jan18 |  -5.49e-07   .0000207    -0.03   0.979    -.0000412    .0000401
         forest_perc |   3.115918   .7508253     4.15   0.000     1.644327    4.587508
          pop_dens18 |   .0021676   .0012967     1.67   0.095    -.0003739    .0047091
foreign_share_1jan18 |   1.024546   3.286135     0.31   0.755    -5.416159    7.465251
               _cons |  -16.44821   2.812171    -5.85   0.000    -21.95997   -10.93646
--------------------------------------------------------------------------------------

. predict pscore
(option pr assumed; Pr(damage_binary))
(32 missing values generated)

. 
. * gen placebo treatment variable
. psmatch2 damage_binary if anno == 2019, pscore(pscore) outcome(party_share) common
----------------------------------------------------------------------------------------
        Variable     Sample |    Treated     Controls   Difference         S.E.   T-stat
----------------------------+-----------------------------------------------------------
     party_share  Unmatched | .473035129    .52782518  -.054790051    .00926683    -5.91
                        ATT | .473035129   .540114898  -.067079769   .014844203    -4.52
----------------------------+-----------------------------------------------------------
Note: S.E. does not take into account that the propensity score is estimated.

           | psmatch2:
 psmatch2: |   Common
 Treatment |  support
assignment | On suppor |     Total
-----------+-----------+----------
 Untreated |       477 |       477 
   Treated |       163 |       163 
-----------+-----------+----------
     Total |       640 |       640 

. bys pro_com: egen _w  = max(_weight)
(1,533 missing values generated)

. drop _weight

. gen placebo = 0 if damage_binary == 0
(657 missing values generated)

. replace placebo = 1 if _w!= . & damage_binary == 0
(397 real changes made)

. drop _w

. 
. * gen IPW for full sample
. sum pscore if damage_binary == 1 & anno == 2019

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      pscore |        163    .4360966    .1328475   .0341655   .7150978

. sum pscore if damage_binary == 0 & anno == 2019

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      pscore |        477    .1926966    .2015376   8.66e-08   .7846277

. gen support = 0 if anno == 2019
(1,925 missing values generated)

. replace support = 1 if pscore >= .0341655 & pscore <= .7150978
(1,757 real changes made)

. gen w_IPW = .
(2,575 missing values generated)

. replace w_IPW = 1/pscore if damage_binary == 1 & anno == 2019
(163 real changes made)

. replace w_IPW = 1/(1-pscore) if damage_binary == 0 & support == 1 & anno == 2019
(279 real changes made)

. bys pro_com: egen _ipw  = max(w_IPW)
(818 missing values generated)

. drop w_IPW

. 
. 
. * estimates
. eststo: xtreg party_share damage_binary##i.anno, fe cl(SLL)
note: 1.damage_binary omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7499                                         min =          2
     Between = 0.0439                                         avg =        4.0
     Overall = 0.2784                                         max =          4

                                                F(6, 51)          =     188.32
corr(u_i, Xb) = -0.0228                         Prob > F          =     0.0000

                                    (Std. err. adjusted for 52 clusters in SLL_2011)
------------------------------------------------------------------------------------
                   |               Robust
       party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
   1.damage_binary |          0  (omitted)
                   |
              anno |
             2009  |   .1109236   .0067016    16.55   0.000     .0974695    .1243776
             2014  |   .0032332   .0037739     0.86   0.396    -.0043433    .0108096
             2019  |    .276035   .0280915     9.83   0.000      .219639    .3324311
                   |
damage_binary#anno |
           1 2009  |  -.0039573   .0086697    -0.46   0.650    -.0213624    .0134478
           1 2014  |  -.0010165   .0074659    -0.14   0.892     -.016005    .0139719
           1 2019  |   .0796756    .027821     2.86   0.006     .0238227    .1355285
                   |
             _cons |   .2177446   .0058707    37.09   0.000     .2059588    .2295304
-------------------+----------------------------------------------------------------
           sigma_u |  .17625129
           sigma_e |  .08136129
               rho |  .82433848   (fraction of variance due to u_i)
------------------------------------------------------------------------------------
(est1 stored)

. eststo: xtreg party_share damage_binary##i.anno [aw=_ipw], fe cl(SLL)
(sum of wgt is 3,647.84491121769)
(sum of wgt is 3,647.84491121769)
(sum of wgt is 3,647.84491121769)
note: 1.damage_binary omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,757
Group variable: pro_com                         Number of groups  =        442

R-squared:                                      Obs per group:
     Within  = 0.7456                                         min =          2
     Between = 0.1302                                         avg =        4.0
     Overall = 0.1734                                         max =          4

                                                F(6, 45)          =     228.29
corr(u_i, Xb) = -0.0624                         Prob > F          =     0.0000

                                    (Std. err. adjusted for 46 clusters in SLL_2011)
------------------------------------------------------------------------------------
                   |               Robust
       party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
   1.damage_binary |          0  (omitted)
                   |
              anno |
             2009  |   .0995429   .0056722    17.55   0.000     .0881186    .1109672
             2014  |   .0080078   .0056621     1.41   0.164    -.0033963     .019412
             2019  |   .2213329   .0389395     5.68   0.000     .1429047    .2997612
                   |
damage_binary#anno |
           1 2009  |    .002799   .0081182     0.34   0.732     -.013552    .0191499
           1 2014  |  -.0008266   .0091624    -0.09   0.929    -.0192807    .0176274
           1 2019  |    .121927   .0384881     3.17   0.003     .0444079    .1994461
                   |
             _cons |   .2104707   .0053336    39.46   0.000     .1997283    .2212131
-------------------+----------------------------------------------------------------
           sigma_u |  .20779979
           sigma_e |  .07976669
               rho |  .87157291   (fraction of variance due to u_i)
------------------------------------------------------------------------------------
(est2 stored)

. eststo: xtreg party_share i.placebo##i.anno i.anno, fe cl(SLL)
note: 1.placebo omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,918
Group variable: pro_com                         Number of groups  =        484

R-squared:                                      Obs per group:
     Within  = 0.6846                                         min =          2
     Between = 0.0013                                         avg =        4.0
     Overall = 0.2393                                         max =          4

                                                F(6, 46)          =      90.46
corr(u_i, Xb) = -0.0041                         Prob > F          =     0.0000

                              (Std. err. adjusted for 47 clusters in SLL_2011)
------------------------------------------------------------------------------
             |               Robust
 party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   1.placebo |          0  (omitted)
             |
        anno |
       2009  |   .1127271   .0077827    14.48   0.000     .0970614    .1283928
       2014  |   .0023924   .0035643     0.67   0.505    -.0047823     .009567
       2019  |   .2823988   .0278957    10.12   0.000     .2262476      .33855
             |
placebo#anno |
     1 2009  |   -.008679   .0087333    -0.99   0.326    -.0262582    .0089003
     1 2014  |    .004131   .0052697     0.78   0.437    -.0064764    .0147383
     1 2019  |   -.030739   .0327123    -0.94   0.352    -.0965853    .0351074
             |
       _cons |   .2520873   .0074203    33.97   0.000      .237151    .2670236
-------------+----------------------------------------------------------------
     sigma_u |  .18403952
     sigma_e |  .08858384
         rho |  .81189979   (fraction of variance due to u_i)
------------------------------------------------------------------------------
(est3 stored)

. 
. * export to R
. keep pro_com SLL_2011 anno party_share placebo damage_binary _ipw pscore

. rename _ipw ipw

. 
. save "placebo_vaia.dta", replace
(file placebo_vaia.dta not found)
file placebo_vaia.dta saved

. 
. ***************************************************************
. * Interaction with Disaster Relief (Exclude Bolzano)
. ***************************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22))
(56,441 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. 
. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. egen fondi_std = std(fondi_wgtd)

. gen fondi_std_t = fondi_std

. replace fondi_std_t = 0 if anno < 2019
(1,579 real changes made)

. 
. est clear

. 
. rename damage_binary_t Damaged

. eststo: xtreg party_share i.Damaged c.fondi_std##i.anno i.cod_prov##i.anno, fe cl(SLL)
note: fondi_std omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9642                                         min =          2
     Between = 0.1518                                         avg =        4.0
     Overall = 0.8313                                         max =          4

                                                F(19, 41)         =    2147.84
corr(u_i, Xb) = 0.0170                          Prob > F          =     0.0000

                                  (Std. err. adjusted for 42 clusters in SLL_2011)
----------------------------------------------------------------------------------
                 |               Robust
     party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
       1.Damaged |   .0258141   .0066846     3.86   0.000     .0123143    .0393138
       fondi_std |          0  (omitted)
                 |
            anno |
           2009  |   .1022809   .0055878    18.30   0.000      .090996    .1135657
           2014  |   .0097366   .0062776     1.55   0.129    -.0029412    .0224144
           2019  |   .3382327   .0112155    30.16   0.000     .3155825    .3608829
                 |
anno#c.fondi_std |
           2009  |   .0007769   .0021828     0.36   0.724    -.0036313    .0051852
           2014  |   .0017925   .0014938     1.20   0.237    -.0012244    .0048094
           2019  |   .0077616   .0020038     3.87   0.000     .0037149    .0118083
                 |
        cod_prov |
             24  |          0  (omitted)
             25  |          0  (omitted)
             30  |          0  (omitted)
             93  |          0  (omitted)
                 |
   cod_prov#anno |
        24 2009  |   .0682605   .0090415     7.55   0.000     .0500008    .0865202
        24 2014  |   -.014606   .0085031    -1.72   0.093    -.0317784    .0025664
        24 2019  |   .0336138    .013381     2.51   0.016     .0065904    .0606371
        25 2009  |   .0244987   .0088668     2.76   0.009     .0065919    .0424056
        25 2014  |  -.0548741   .0098364    -5.58   0.000    -.0747392    -.035009
        25 2019  |  -.0229731    .013913    -1.65   0.106     -.051071    .0051247
        30 2009  |  -.0076494   .0071534    -1.07   0.291     -.022096    .0067971
        30 2014  |  -.0047673   .0069273    -0.69   0.495    -.0187573    .0092228
        30 2019  |     .05001   .0140463     3.56   0.001     .0216429    .0783771
        93 2009  |   .0124587   .0085022     1.47   0.150    -.0047118    .0296293
        93 2014  |  -.0254875   .0073207    -3.48   0.001     -.040272   -.0107031
        93 2019  |    .020802   .0136152     1.53   0.134    -.0066945    .0482985
                 |
           _cons |   .1279688    .001691    75.68   0.000     .1245538    .1313837
-----------------+----------------------------------------------------------------
         sigma_u |  .06246751
         sigma_e |  .03387305
             rho |  .77277618   (fraction of variance due to u_i)
----------------------------------------------------------------------------------
(est1 stored)

. eststo: xtreg party_share i.Damaged##c.fondi_std c.fondi_std##i.anno i.cod_prov##i.anno, fe cl(SLL)
note: fondi_std omitted because of collinearity
note: fondi_std omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9642                                         min =          2
     Between = 0.1514                                         avg =        4.0
     Overall = 0.8312                                         max =          4

                                                F(20, 41)         =    2126.12
corr(u_i, Xb) = 0.0170                          Prob > F          =     0.0000

                                     (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------------
                    |               Robust
        party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          1.Damaged |   .0258297   .0066611     3.88   0.000     .0123774     .039282
          fondi_std |          0  (omitted)
                    |
Damaged#c.fondi_std |
                 1  |  -.0014875   .0034718    -0.43   0.671     -.008499     .005524
                    |
          fondi_std |          0  (omitted)
                    |
               anno |
              2009  |   .1022804    .005589    18.30   0.000     .0909932    .1135675
              2014  |   .0097368   .0062793     1.55   0.129    -.0029445    .0224181
              2019  |   .3382767   .0112154    30.16   0.000     .3156266    .3609267
                    |
   anno#c.fondi_std |
              2009  |   .0007771   .0021833     0.36   0.724    -.0036323    .0051864
              2014  |   .0017925   .0014943     1.20   0.237    -.0012252    .0048103
              2019  |   .0090436   .0031888     2.84   0.007     .0026037    .0154836
                    |
           cod_prov |
                24  |          0  (omitted)
                25  |          0  (omitted)
                30  |          0  (omitted)
                93  |          0  (omitted)
                    |
      cod_prov#anno |
           24 2009  |    .068261   .0090435     7.55   0.000     .0499972    .0865248
           24 2014  |  -.0146065   .0085054    -1.72   0.093    -.0317835    .0025705
           24 2019  |   .0339063   .0135085     2.51   0.016     .0066253    .0611873
           25 2009  |   .0244992   .0088687     2.76   0.009     .0065884      .04241
           25 2014  |  -.0548775   .0098409    -5.58   0.000    -.0747517   -.0350033
           25 2019  |  -.0228523   .0139706    -1.64   0.110    -.0510665    .0053619
           30 2009  |  -.0076496   .0071551    -1.07   0.291    -.0220995    .0068004
           30 2014  |  -.0047685   .0069297    -0.69   0.495    -.0187632    .0092262
           30 2019  |   .0502361   .0140874     3.57   0.001      .021786    .0786863
           93 2009  |   .0124593    .008504     1.47   0.151    -.0047149    .0296334
           93 2014  |  -.0254877   .0073227    -3.48   0.001    -.0402762   -.0106993
           93 2019  |   .0210661    .013731     1.53   0.133    -.0066643    .0487965
                    |
              _cons |   .1279692   .0016917    75.65   0.000     .1245528    .1313855
--------------------+----------------------------------------------------------------
            sigma_u |  .06247444
            sigma_e |  .03388299
                rho |  .77271201   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------
(est2 stored)

. rename Damaged damage_binary_t

. 
. rename damage_mean_t Damaged

. eststo: xtreg party_share c.Damaged c.fondi_std##i.anno i.cod_prov##i.anno, fe cl(SLL) 
note: fondi_std omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9637                                         min =          2
     Between = 0.1478                                         avg =        4.0
     Overall = 0.8302                                         max =          4

                                                F(19, 41)         =    2126.98
corr(u_i, Xb) = 0.0164                          Prob > F          =     0.0000

                                  (Std. err. adjusted for 42 clusters in SLL_2011)
----------------------------------------------------------------------------------
                 |               Robust
     party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
         Damaged |   .1187741   .0732905     1.62   0.113    -.0292391    .2667873
       fondi_std |          0  (omitted)
                 |
            anno |
           2009  |   .1022836   .0055907    18.30   0.000     .0909931    .1135742
           2014  |   .0096861   .0062737     1.54   0.130     -.002984    .0223561
           2019  |   .3550689   .0090681    39.16   0.000     .3367554    .3733824
                 |
anno#c.fondi_std |
           2009  |   .0007725   .0021888     0.35   0.726    -.0036478    .0051929
           2014  |    .001799   .0014928     1.21   0.235    -.0012158    .0048138
           2019  |   .0080075   .0022173     3.61   0.001     .0035295    .0124854
                 |
        cod_prov |
             24  |          0  (omitted)
             25  |          0  (omitted)
             30  |          0  (omitted)
             93  |          0  (omitted)
                 |
   cod_prov#anno |
        24 2009  |   .0682594   .0090467     7.55   0.000     .0499893    .0865295
        24 2014  |  -.0145384   .0085035    -1.71   0.095    -.0317116    .0026349
        24 2019  |   .0177854   .0118115     1.51   0.140    -.0060685    .0416392
        25 2009  |   .0244953   .0088701     2.76   0.009     .0065817    .0424089
        25 2014  |  -.0547149   .0098067    -5.58   0.000      -.07452   -.0349097
        25 2019  |  -.0332713   .0140784    -2.36   0.023    -.0617032   -.0048393
        30 2009  |  -.0076485   .0071568    -1.07   0.291    -.0221019     .006805
        30 2014  |  -.0047087   .0069234    -0.68   0.500    -.0186908    .0092734
        30 2019  |   .0338413   .0132502     2.55   0.014     .0070821    .0606006
        93 2009  |   .0124548   .0085056     1.46   0.151    -.0047226    .0296322
        93 2014  |  -.0254354   .0073185    -3.48   0.001    -.0402153   -.0106554
        93 2019  |   .0060578   .0130412     0.46   0.645    -.0202794    .0323949
                 |
           _cons |   .1279674    .001703    75.14   0.000     .1245281    .1314067
-----------------+----------------------------------------------------------------
         sigma_u |  .06258019
         sigma_e |   .0341147
             rho |  .77090717   (fraction of variance due to u_i)
----------------------------------------------------------------------------------
(est3 stored)

. eststo: xtreg party_share c.Damaged##c.fondi_std c.fondi_std##i.anno i.cod_prov##i.anno, fe cl(SLL)
note: fondi_std omitted because of collinearity
note: fondi_std omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9641                                         min =          2
     Between = 0.1490                                         avg =        4.0
     Overall = 0.8307                                         max =          4

                                                F(20, 41)         =    3645.35
corr(u_i, Xb) = 0.0164                          Prob > F          =     0.0000

                                       (Std. err. adjusted for 42 clusters in SLL_2011)
---------------------------------------------------------------------------------------
                      |               Robust
          party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
              Damaged |   .2016018   .0714384     2.82   0.007     .0573291    .3458745
            fondi_std |          0  (omitted)
                      |
c.Damaged#c.fondi_std |  -.0860865   .0154875    -5.56   0.000    -.1173641   -.0548089
                      |
            fondi_std |          0  (omitted)
                      |
                 anno |
                2009  |   .1022664   .0055884    18.30   0.000     .0909803    .1135525
                2014  |   .0096424   .0062761     1.54   0.132    -.0030325    .0223174
                2019  |   .3524467   .0091144    38.67   0.000     .3340397    .3708536
                      |
     anno#c.fondi_std |
                2009  |   .0007774   .0021877     0.36   0.724    -.0036408    .0051955
                2014  |   .0018105   .0014931     1.21   0.232    -.0012048    .0048259
                2019  |   .0154706   .0031435     4.92   0.000     .0091222    .0218189
                      |
             cod_prov |
                  24  |          0  (omitted)
                  25  |          0  (omitted)
                  30  |          0  (omitted)
                  93  |          0  (omitted)
                      |
        cod_prov#anno |
             24 2009  |   .0682773   .0090459     7.55   0.000     .0500088    .0865459
             24 2014  |  -.0144946    .008506    -1.70   0.096    -.0316727    .0026836
             24 2019  |   .0222863   .0119145     1.87   0.069    -.0017754    .0463481
             25 2009  |   .0245132   .0088695     2.76   0.009      .006601    .0424255
             25 2014  |  -.0546962    .009815    -5.57   0.000     -.074518   -.0348744
             25 2019  |  -.0301819   .0139208    -2.17   0.036    -.0582955   -.0020683
             30 2009  |  -.0076355   .0071559    -1.07   0.292    -.0220871     .006816
             30 2014  |  -.0046706   .0069246    -0.67   0.504    -.0186551    .0093139
             30 2019  |   .0378634   .0128746     2.94   0.005     .0118627    .0638641
             93 2009  |   .0124733   .0085048     1.47   0.150    -.0047024     .029649
             93 2014  |  -.0253888   .0073215    -3.47   0.001    -.0401749   -.0106026
             93 2019  |   .0105619   .0130849     0.81   0.424    -.0158636    .0369874
                      |
                _cons |   .1279782   .0016882    75.81   0.000     .1245688    .1313877
----------------------+----------------------------------------------------------------
              sigma_u |   .0625487
              sigma_e |  .03395146
                  rho |   .7724201   (fraction of variance due to u_i)
---------------------------------------------------------------------------------------
(est4 stored)

. rename Damaged damage_mean_t

. 
. rename damage_max_t Damaged

. eststo: xtreg party_share c.Damaged c.fondi_std##i.anno i.cod_prov##i.anno, fe cl(SLL)
note: fondi_std omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9644                                         min =          2
     Between = 0.1527                                         avg =        4.0
     Overall = 0.8316                                         max =          4

                                                F(19, 41)         =    2212.24
corr(u_i, Xb) = 0.0172                          Prob > F          =     0.0000

                                  (Std. err. adjusted for 42 clusters in SLL_2011)
----------------------------------------------------------------------------------
                 |               Robust
     party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
         Damaged |   .0324408   .0071833     4.52   0.000     .0179339    .0469478
       fondi_std |          0  (omitted)
                 |
            anno |
           2009  |   .1022762    .005586    18.31   0.000      .090995    .1135575
           2014  |   .0097731   .0062764     1.56   0.127    -.0029022    .0224485
           2019  |   .3394509   .0101322    33.50   0.000     .3189885    .3599132
                 |
anno#c.fondi_std |
           2009  |    .000777   .0021842     0.36   0.724    -.0036341    .0051882
           2014  |   .0017831   .0014979     1.19   0.241    -.0012419    .0048081
           2019  |   .0070237   .0017763     3.95   0.000     .0034363     .010611
                 |
        cod_prov |
             24  |          0  (omitted)
             25  |          0  (omitted)
             30  |          0  (omitted)
             93  |          0  (omitted)
                 |
   cod_prov#anno |
        24 2009  |   .0682643   .0090405     7.55   0.000     .0500067    .0865219
        24 2014  |  -.0146501   .0085017    -1.72   0.092    -.0318196    .0025194
        24 2019  |   .0318957   .0123244     2.59   0.013     .0070061    .0567853
        25 2009  |   .0245034   .0088656     2.76   0.009     .0065989    .0424079
        25 2014  |  -.0549251   .0098384    -5.58   0.000    -.0747941   -.0350561
        25 2019  |  -.0251825   .0130142    -1.93   0.060    -.0514652    .0011003
        30 2009  |  -.0076458   .0071524    -1.07   0.291    -.0220903    .0067988
        30 2014  |  -.0048073   .0069275    -0.69   0.492    -.0187977    .0091831
        30 2019  |   .0484469   .0130879     3.70   0.001     .0220154    .0748784
        93 2009  |   .0124634   .0085015     1.47   0.150    -.0047057    .0296325
        93 2014  |  -.0255265   .0073194    -3.49   0.001    -.0403084   -.0107447
        93 2019  |   .0192215    .012703     1.51   0.138    -.0064327    .0448758
                 |
           _cons |   .1279654   .0016694    76.65   0.000      .124594    .1313368
-----------------+----------------------------------------------------------------
         sigma_u |    .062431
         sigma_e |  .03378451
             rho |  .77348918   (fraction of variance due to u_i)
----------------------------------------------------------------------------------
(est5 stored)

. eststo: xtreg party_share c.Damaged##c.fondi_std c.fondi_std##i.anno i.cod_prov##i.anno, fe cl(SLL)
note: fondi_std omitted because of collinearity
note: fondi_std omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9644                                         min =          2
     Between = 0.1510                                         avg =        4.0
     Overall = 0.8315                                         max =          4

                                                F(20, 41)         =    2238.24
corr(u_i, Xb) = 0.0170                          Prob > F          =     0.0000

                                       (Std. err. adjusted for 42 clusters in SLL_2011)
---------------------------------------------------------------------------------------
                      |               Robust
          party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
              Damaged |    .032687   .0070218     4.66   0.000     .0185062    .0468678
            fondi_std |          0  (omitted)
                      |
c.Damaged#c.fondi_std |  -.0066363   .0045289    -1.47   0.150    -.0157826      .00251
                      |
            fondi_std |          0  (omitted)
                      |
                 anno |
                2009  |   .1022746   .0055869    18.31   0.000     .0909915    .1135577
                2014  |   .0097757   .0062784     1.56   0.127    -.0029039    .0224553
                2019  |   .3395537   .0101127    33.58   0.000     .3191307    .3599766
                      |
     anno#c.fondi_std |
                2009  |   .0007777   .0021845     0.36   0.724     -.003634    .0051894
                2014  |    .001783   .0014987     1.19   0.241    -.0012436    .0048096
                2019  |   .0121318   .0039921     3.04   0.004     .0040695    .0201941
                      |
             cod_prov |
                  24  |          0  (omitted)
                  25  |          0  (omitted)
                  30  |          0  (omitted)
                  93  |          0  (omitted)
                      |
        cod_prov#anno |
             24 2009  |   .0682658   .0090422     7.55   0.000     .0500048    .0865268
             24 2014  |  -.0146541   .0085041    -1.72   0.092    -.0318285    .0025203
             24 2019  |   .0331169   .0124351     2.66   0.011     .0080036    .0582301
             25 2009  |   .0245051   .0088674     2.76   0.009     .0065971    .0424131
             25 2014  |  -.0549407   .0098435    -5.58   0.000      -.07482   -.0350615
             25 2019  |   -.024655   .0130477    -1.89   0.066    -.0510053    .0016953
             30 2009  |  -.0076467   .0071542    -1.07   0.291    -.0220948    .0068014
             30 2014  |  -.0048138   .0069298    -0.69   0.491    -.0188088    .0091812
             30 2019  |   .0494237   .0129771     3.81   0.000      .023216    .0756315
             93 2009  |   .0124652   .0085031     1.47   0.150    -.0047071    .0296375
             93 2014  |  -.0255291   .0073219    -3.49   0.001    -.0403159   -.0107423
             93 2019  |   .0203385   .0127586     1.59   0.119    -.0054281    .0461051
                      |
                _cons |   .1279667   .0016698    76.64   0.000     .1245945    .1313389
----------------------+----------------------------------------------------------------
              sigma_u |  .06245904
              sigma_e |   .0337777
                  rho |  .77371716   (fraction of variance due to u_i)
---------------------------------------------------------------------------------------
(est6 stored)

. rename Damaged damage_max_t

. 
. esttab using "table1_interaction_fondi.tex", replace b(%8.3f) se(%8.3f) noomitted nobaselev stats(year_fe municipality_fe prov_trend ymean N r2 
> measure,  fmt(0 2))  star(+ 0.10 * 0.05 ** 0.01 *** 0.001)
(file table1_interaction_fondi.tex not found)
(output written to table1_interaction_fondi.tex)

. 
. 
. ************************************************************
. * Table of Pre-post DID Estimates on vote for Regional Incumbent
. ************************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22)) | (party == "SVP" & cod_prov == 21)
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. est clear

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_mean if anno == 2019
(166 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_mean if anno == 2009
(164 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_mean if anno == 2004
(161 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov if anno > 2009, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,300
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9739                                         min =          2
     Between = 0.6776                                         avg =        2.0
     Overall = 0.1880                                         max =          2

                                                F(7, 51)          =    1526.17
corr(u_i, Xb) = -0.4005                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .2080523   .0893526     2.33   0.024     .0286695    .3874352
              |
         anno |
        2019  |  -.0513162   .0034406   -14.92   0.000    -.0582234   -.0444089
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 22  |   .3977171   .0122324    32.51   0.000     .3731596    .4222746
     2019 24  |   .4271468   .0073155    58.39   0.000     .4124603    .4418333
     2019 25  |   .4166614   .0138731    30.03   0.000       .38881    .4445128
     2019 30  |   .4339054   .0085122    50.97   0.000     .4168164    .4509945
     2019 93  |   .4265746   .0086852    49.12   0.000     .4091384    .4440109
              |
        _cons |   .2205243   .0019632   112.33   0.000     .2165831    .2244655
--------------+----------------------------------------------------------------
      sigma_u |  .21987231
      sigma_e |  .03894536
          rho |  .96958035   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est1 stored)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9583                                         min =          2
     Between = 0.6507                                         avg =        4.0
     Overall = 0.1714                                         max =          4

                                                F(19, 51)         =    2211.82
corr(u_i, Xb) = -0.2432                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .2008899   .0638957     3.14   0.003      .072614    .3291659
              |
         anno |
        2009  |   .0696259   .0055314    12.59   0.000     .0585211    .0807308
        2014  |   .0326488   .0064543     5.06   0.000     .0196913    .0456063
        2019  |  -.0186654   .0065993    -2.83   0.007    -.0319142   -.0054167
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0330315   .0076253     4.33   0.000      .017723      .04834
     2009 24  |   .1007027   .0088482    11.38   0.000     .0829392    .1184662
     2009 25  |    .057047   .0087158     6.55   0.000     .0395493    .0745446
     2009 30  |   .0248632   .0069131     3.60   0.001     .0109847    .0387417
     2009 93  |   .0449146   .0082747     5.43   0.000     .0283024    .0615269
     2014 22  |  -.0221036   .0088447    -2.50   0.016      -.03986   -.0043472
     2014 24  |  -.0380019   .0084789    -4.48   0.000     -.055024   -.0209798
     2014 25  |  -.0779198   .0092934    -8.38   0.000     -.096577   -.0592626
     2014 30  |  -.0280178   .0070027    -4.00   0.000    -.0420763   -.0139593
     2014 93  |  -.0488589   .0073062    -6.69   0.000    -.0635266   -.0341912
     2019 22  |   .3757521   .0112478    33.41   0.000     .3531711    .3983331
     2019 24  |   .3891555   .0097285    40.00   0.000     .3696248    .4086863
     2019 25  |   .3387878   .0121645    27.85   0.000     .3143666    .3632091
     2019 30  |   .4058952   .0120548    33.67   0.000     .3816943    .4300962
     2019 93  |    .377716   .0112554    33.56   0.000     .3551197    .4003122
              |
        _cons |    .217658   .0016229   134.12   0.000     .2143999    .2209161
--------------+----------------------------------------------------------------
      sigma_u |  .20745724
      sigma_e |  .03335274
          rho |  .97480447   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est2 stored)

. eststo: xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9583                                         min =          2
     Between = 0.6444                                         avg =        4.0
     Overall = 0.1729                                         max =          4

                                                F(21, 51)         =    1998.65
corr(u_i, Xb) = -0.2414                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .2080523   .0894773     2.33   0.024     .0284192    .3876855
 Damaged_2009 |   .0946083   .0831691     1.14   0.261    -.0723606    .2615772
 Damaged_2004 |  -.0733914   .0792972    -0.93   0.359    -.2325871    .0858044
              |
         anno |
        2009  |   .0695821   .0055503    12.54   0.000     .0584394    .0807249
        2014  |   .0326305   .0064583     5.05   0.000     .0196649    .0455962
        2019  |  -.0186856   .0066033    -2.83   0.007    -.0319424   -.0054289
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0297231   .0079717     3.73   0.000     .0137193    .0457269
     2009 24  |   .1004428   .0087838    11.43   0.000     .0828085    .1180771
     2009 25  |   .0559227   .0083412     6.70   0.000     .0391771    .0726683
     2009 30  |    .024678   .0069475     3.55   0.001     .0107304    .0386256
     2009 93  |   .0449072   .0082985     5.41   0.000     .0282473    .0615671
     2014 22  |  -.0235664   .0092212    -2.56   0.014    -.0420786   -.0050541
     2014 24  |  -.0381175   .0084776    -4.50   0.000    -.0551369    -.021098
     2014 25  |  -.0784126   .0094528    -8.30   0.000    -.0973899   -.0594354
     2014 30  |  -.0281015   .0069903    -4.02   0.000    -.0421352   -.0140678
     2014 93  |   -.048863   .0073009    -6.69   0.000    -.0635201   -.0342059
     2019 22  |   .3741507   .0111743    33.48   0.000     .3517173    .3965841
     2019 24  |   .3890294   .0097208    40.02   0.000      .369514    .4085447
     2019 25  |   .3382488    .012027    28.12   0.000     .3141036    .3623939
     2019 30  |   .4058039   .0120132    33.78   0.000     .3816864    .4299215
     2019 93  |   .3777116    .011249    33.58   0.000     .3551282     .400295
              |
        _cons |   .2181528   .0017556   124.26   0.000     .2146283    .2216774
--------------+----------------------------------------------------------------
      sigma_u |  .20717167
      sigma_e |  .03333997
          rho |  .97475558   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est3 stored)

. 
. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_max if anno == 2019
(166 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_max if anno == 2009
(164 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_max if anno == 2004
(161 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov if anno > 2009, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,300
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9748                                         min =          2
     Between = 0.6701                                         avg =        2.0
     Overall = 0.1890                                         max =          2

                                                F(7, 51)          =    2184.76
corr(u_i, Xb) = -0.4001                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0384819   .0088222     4.36   0.000     .0207706    .0561933
              |
         anno |
        2019  |  -.0523948    .003435   -15.25   0.000    -.0592908   -.0454988
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 22  |   .3809714   .0140253    27.16   0.000     .3528145    .4091283
     2019 24  |   .4269017   .0070286    60.74   0.000     .4127912    .4410123
     2019 25  |   .4095694   .0104337    39.25   0.000      .388623    .4305159
     2019 30  |   .4341127   .0080241    54.10   0.000     .4180037    .4502218
     2019 93  |   .4250614   .0082159    51.74   0.000     .4085674    .4415555
              |
        _cons |   .2205243   .0018276   120.66   0.000     .2168552    .2241934
--------------+----------------------------------------------------------------
      sigma_u |  .21976383
      sigma_e |  .03829234
          rho |  .97053393   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est4 stored)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9590                                         min =          2
     Between = 0.6452                                         avg =        4.0
     Overall = 0.1719                                         max =          4

                                                F(19, 51)         =    2165.50
corr(u_i, Xb) = -0.2428                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0334648   .0074647     4.48   0.000     .0184787    .0484508
              |
         anno |
        2009  |    .069695   .0055084    12.65   0.000     .0586364    .0807536
        2014  |   .0327179   .0064467     5.08   0.000     .0197755    .0456602
        2019  |   -.019529   .0066694    -2.93   0.005    -.0329184   -.0061395
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0329609   .0076081     4.33   0.000     .0176869    .0482349
     2009 24  |   .1006302   .0088317    11.39   0.000     .0828998    .1183605
     2009 25  |   .0569779    .008702     6.55   0.000     .0395079    .0744478
     2009 30  |   .0247885   .0068941     3.60   0.001      .010948    .0386289
     2009 93  |   .0448456   .0082589     5.43   0.000     .0282651    .0614261
     2014 22  |  -.0220839   .0088343    -2.50   0.016    -.0398196   -.0043482
     2014 24  |  -.0380895   .0084696    -4.50   0.000    -.0550929   -.0210861
     2014 25  |   -.078107   .0093109    -8.39   0.000    -.0967995   -.0594146
     2014 30  |  -.0280953   .0069953    -4.02   0.000     -.042139   -.0140516
     2014 93  |   -.048928   .0072983    -6.70   0.000      -.06358    -.034276
     2019 22  |   .3615956   .0121884    29.67   0.000     .3371264    .3860648
     2019 24  |   .3888843   .0095976    40.52   0.000     .3696164    .4081522
     2019 25  |   .3325621   .0105509    31.52   0.000     .3113803    .3537439
     2019 30  |   .4060193   .0117144    34.66   0.000     .3825017    .4295369
     2019 93  |   .3763317   .0103872    36.23   0.000     .3554785    .3971849
              |
        _cons |   .2176453   .0016125   134.97   0.000      .214408    .2208826
--------------+----------------------------------------------------------------
      sigma_u |  .20740052
      sigma_e |  .03307603
          rho |  .97519726   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est5 stored)

. eststo: xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9590                                         min =          2
     Between = 0.6508                                         avg =        4.0
     Overall = 0.1694                                         max =          4

                                                F(21, 51)         =    2053.52
corr(u_i, Xb) = -0.2461                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0384819   .0088345     4.36   0.000     .0207459     .056218
 Damaged_2009 |    .009981   .0098014     1.02   0.313    -.0096961    .0296581
 Damaged_2004 |    .005157   .0060752     0.85   0.400    -.0070394    .0173534
              |
         anno |
        2009  |   .0695518   .0055685    12.49   0.000     .0583725     .080731
        2014  |    .032869   .0064252     5.12   0.000     .0199698    .0457681
        2019  |  -.0195258   .0066729    -2.93   0.005    -.0329222   -.0061294
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0303796   .0080392     3.78   0.000     .0142401     .046519
     2009 24  |   .1005562    .008836    11.38   0.000     .0828172    .1182952
     2009 25  |   .0558808   .0084422     6.62   0.000     .0389324    .0728293
     2009 30  |   .0247867   .0069571     3.56   0.001     .0108197    .0387538
     2009 93  |    .044656   .0083907     5.32   0.000     .0278109     .061501
     2014 22  |  -.0193107   .0092904    -2.08   0.043     -.037962   -.0006595
     2014 24  |  -.0380112   .0084891    -4.48   0.000    -.0550538   -.0209686
     2014 25  |  -.0769534   .0092164    -8.35   0.000    -.0954561   -.0584506
     2014 30  |  -.0280917   .0070211    -4.00   0.000    -.0421871   -.0139963
     2014 93  |  -.0487232    .007408    -6.58   0.000    -.0635955    -.033851
     2019 22  |   .3616607   .0122905    29.43   0.000     .3369865    .3863348
     2019 24  |   .3888905   .0096045    40.49   0.000     .3696086    .4081724
     2019 25  |   .3326161   .0106876    31.12   0.000     .3111599    .3540723
     2019 30  |    .406021   .0117239    34.63   0.000     .3824844    .4295577
     2019 93  |   .3763382   .0103922    36.21   0.000      .355475    .3972013
              |
        _cons |   .2166108   .0017975   120.50   0.000     .2130021    .2202195
--------------+----------------------------------------------------------------
      sigma_u |  .20790089
      sigma_e |  .03307306
          rho |   .9753179   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est6 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_binary if anno == 2019
(166 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_binary if anno == 2009
(164 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_binary if anno == 2004
(161 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov if anno > 2009, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,300
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9745                                         min =          2
     Between = 0.6724                                         avg =        2.0
     Overall = 0.1887                                         max =          2

                                                F(7, 51)          =    1880.26
corr(u_i, Xb) = -0.4003                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0300795   .0075019     4.01   0.000     .0150188    .0451403
              |
         anno |
        2019  |  -.0525566   .0034218   -15.36   0.000    -.0594261   -.0456871
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 22  |   .3805224   .0143766    26.47   0.000     .3516602    .4093847
     2019 24  |    .427432   .0070385    60.73   0.000     .4133017    .4415624
     2019 25  |   .4109181   .0108126    38.00   0.000     .3892109    .4326254
     2019 30  |   .4345253   .0081226    53.50   0.000     .4182186     .450832
     2019 93  |   .4254721   .0082153    51.79   0.000     .4089791     .441965
              |
        _cons |   .2205243   .0018692   117.98   0.000     .2167717     .224277
--------------+----------------------------------------------------------------
      sigma_u |  .21979798
      sigma_e |  .03849741
          rho |  .97023588   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est7 stored)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9587                                         min =          2
     Between = 0.6471                                         avg =        4.0
     Overall = 0.1718                                         max =          4

                                                F(19, 51)         =    2064.73
corr(u_i, Xb) = -0.2429                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0254904    .006906     3.69   0.001      .011626    .0393549
              |
         anno |
        2009  |   .0696931   .0055102    12.65   0.000     .0586309    .0807553
        2014  |    .032716   .0064474     5.07   0.000     .0197723    .0456596
        2019  |  -.0196428   .0066586    -2.95   0.005    -.0330104   -.0062752
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0329703   .0076113     4.33   0.000       .01769    .0482506
     2009 24  |   .1006332   .0088329    11.39   0.000     .0829004    .1183659
     2009 25  |   .0569798   .0087024     6.55   0.000     .0395091    .0744505
     2009 30  |   .0247922   .0068955     3.60   0.001     .0109489    .0386356
     2009 93  |   .0448475   .0082601     5.43   0.000     .0282646    .0614303
     2014 22  |  -.0221111   .0088373    -2.50   0.016    -.0398528   -.0043694
     2014 24  |  -.0380818   .0084712    -4.50   0.000    -.0550883   -.0210752
     2014 25  |  -.0780845   .0093086    -8.39   0.000    -.0967724   -.0593966
     2014 30  |  -.0280906   .0069962    -4.02   0.000    -.0421361   -.0140451
     2014 93  |  -.0489261   .0072986    -6.70   0.000    -.0635786   -.0342735
     2019 22  |   .3616488   .0130717    27.67   0.000     .3354063    .3878913
     2019 24  |   .3893537   .0096301    40.43   0.000     .3700205    .4086869
     2019 25  |   .3339148   .0108085    30.89   0.000     .3122158    .3556138
     2019 30  |   .4063739    .011816    34.39   0.000     .3826523    .4300954
     2019 93  |   .3767153    .010477    35.96   0.000     .3556819    .3977487
              |
        _cons |   .2176471   .0016292   133.59   0.000     .2143763    .2209178
--------------+----------------------------------------------------------------
      sigma_u |  .20741094
      sigma_e |  .03317919
          rho |  .97504862   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est8 stored)

. eststo: xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9587                                         min =          2
     Between = 0.6615                                         avg =        4.0
     Overall = 0.1672                                         max =          4

                                                F(21, 51)         =    2059.28
corr(u_i, Xb) = -0.2487                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0300795   .0075124     4.00   0.000     .0149977    .0451613
 Damaged_2009 |   .0069131    .008264     0.84   0.407    -.0096775    .0235037
 Damaged_2004 |   .0069797   .0055151     1.27   0.211    -.0040923    .0180518
              |
         anno |
        2009  |   .0696708   .0055273    12.60   0.000     .0585742    .0807673
        2014  |   .0329916   .0064185     5.14   0.000     .0201059    .0458773
        2019  |   -.019565   .0066566    -2.94   0.005    -.0329287   -.0062012
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0330467   .0078367     4.22   0.000     .0173139    .0487795
     2009 24  |   .1006598   .0088456    11.38   0.000     .0829014    .1184181
     2009 25  |   .0570214     .00871     6.55   0.000     .0395352    .0745075
     2009 30  |   .0248188   .0069101     3.59   0.001     .0109461    .0386914
     2009 93  |   .0448752   .0082785     5.42   0.000     .0282555    .0614948
     2014 22  |  -.0171711    .009223    -1.86   0.068    -.0356871    .0013448
     2014 24  |  -.0380445   .0084769    -4.49   0.000    -.0550625   -.0210264
     2014 25  |  -.0763707   .0090962    -8.40   0.000    -.0946321   -.0581093
     2014 30  |  -.0281547   .0070281    -4.01   0.000    -.0422641   -.0140452
     2014 93  |  -.0486433   .0074771    -6.51   0.000    -.0636543   -.0336324
     2019 22  |   .3633513   .0130001    27.95   0.000     .3372526      .38945
     2019 24  |   .3893876    .009643    40.38   0.000     .3700284    .4087467
     2019 25  |   .3345475   .0110693    30.22   0.000      .312325    .3567699
     2019 30  |   .4063706   .0118526    34.29   0.000     .3825755    .4301657
     2019 93  |   .3768287   .0105406    35.75   0.000     .3556677    .3979898
              |
        _cons |   .2158674   .0018678   115.57   0.000     .2121176    .2196172
--------------+----------------------------------------------------------------
      sigma_u |  .20831254
      sigma_e |  .03318089
          rho |  .97525633   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est9 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. esttab using "ax-tab_main_results_incumbent.tex", keep(Damaged_*)  replace b(%8.3f) se(%8.3f) noomitted nobaselev stats(N,  fmt(0 0))  star(+ 0.
> 10 * 0.05 ** 0.01 *** 0.001)
(file ax-tab_main_results_incumbent.tex not found)
(output written to ax-tab_main_results_incumbent.tex)

. 
. *******************************************************
. *  Table of Pre-post DID Estimates on vote for the Green
. *******************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if party == "green" 
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. keep if anno == 2004 | anno == 2014 | anno == 2019
(642 observations deleted)

. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. est clear

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_mean if anno == 2019
(166 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_mean if anno == 2004
(161 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov if anno > 2009, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,300
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7607                                         min =          2
     Between = 0.6894                                         avg =        2.0
     Overall = 0.5162                                         max =          2

                                                F(7, 51)          =     337.79
corr(u_i, Xb) = 0.2683                          Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.0257356   .0186553    -1.38   0.174    -.0631876    .0117164
              |
         anno |
        2019  |   .0396103   .0021186    18.70   0.000     .0353571    .0438635
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 22  |  -.0184116   .0028947    -6.36   0.000     -.024223   -.0126002
     2019 24  |  -.0238535   .0023478   -10.16   0.000    -.0285669     -.01914
     2019 25  |  -.0252863   .0027761    -9.11   0.000    -.0308596   -.0197129
     2019 30  |  -.0245088   .0021864   -11.21   0.000    -.0288981   -.0201195
     2019 93  |  -.0258415   .0021712   -11.90   0.000    -.0302004   -.0214827
              |
        _cons |   .0148534   .0003395    43.75   0.000     .0141719     .015535
--------------+----------------------------------------------------------------
      sigma_u |   .0149597
      sigma_e |  .00908365
          rho |  .73061939   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est1 stored)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,933
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7208                                         min =          2
     Between = 0.7699                                         avg =        3.0
     Overall = 0.0078                                         max =          3

                                                F(13, 51)         =     498.28
corr(u_i, Xb) = -0.6739                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.0235782   .0276685    -0.85   0.398     -.079125    .0319686
              |
         anno |
        2014  |   -.108162   .0133247    -8.12   0.000    -.1349124   -.0814116
        2019  |  -.0685523   .0133881    -5.12   0.000    -.0954301   -.0416745
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2014 22  |   .0845498   .0134722     6.28   0.000     .0575033    .1115964
     2014 24  |   .0867822   .0134336     6.46   0.000     .0598132    .1137512
     2014 25  |   .0927973   .0133496     6.95   0.000     .0659969    .1195977
     2014 30  |   .0947741   .0133558     7.10   0.000     .0679613     .121587
     2014 93  |   .0935704   .0133454     7.01   0.000     .0667784    .1203623
     2019 22  |   .0660965   .0136291     4.85   0.000     .0387349    .0934582
     2019 24  |   .0629255   .0135305     4.65   0.000     .0357618    .0900893
     2019 25  |   .0674971   .0134508     5.02   0.000     .0404935    .0945007
     2019 30  |    .070263   .0134271     5.23   0.000      .043307     .097219
     2019 93  |   .0677287   .0134355     5.04   0.000     .0407558    .0947017
              |
        _cons |   .0496189   .0016624    29.85   0.000     .0462815    .0529563
--------------+----------------------------------------------------------------
      sigma_u |  .04747901
      sigma_e |   .0156495
          rho |  .90200449   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est2 stored)

. eststo: xtreg party_share Damaged_2019 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,933
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7208                                         min =          2
     Between = 0.7701                                         avg =        3.0
     Overall = 0.0078                                         max =          3

                                                F(14, 51)         =     493.60
corr(u_i, Xb) = -0.6737                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.0257356   .0186727    -1.38   0.174    -.0632226    .0117515
 Damaged_2004 |  -.0043299   .0443246    -0.10   0.923    -.0933153    .0846555
              |
         anno |
        2014  |  -.1081631   .0133281    -8.12   0.000    -.1349204   -.0814057
        2019  |  -.0685528   .0133915    -5.12   0.000    -.0954373   -.0416683
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2014 22  |   .0844646   .0135588     6.23   0.000     .0572442     .111685
     2014 24  |   .0867756   .0134356     6.46   0.000     .0598025    .1137486
     2014 25  |   .0927686   .0133486     6.95   0.000     .0659702    .1195669
     2014 30  |   .0947693   .0133576     7.09   0.000     .0679528    .1215859
     2014 93  |   .0935702   .0133485     7.01   0.000      .066772    .1203684
     2019 22  |    .066053   .0136648     4.83   0.000     .0386197    .0934864
     2019 24  |   .0629221   .0135341     4.65   0.000     .0357513    .0900928
     2019 25  |   .0674823   .0134567     5.01   0.000     .0404668    .0944978
     2019 30  |   .0702605   .0134302     5.23   0.000     .0432982    .0972228
     2019 93  |   .0677286   .0134388     5.04   0.000     .0407491    .0947082
              |
        _cons |   .0496478   .0017197    28.87   0.000     .0461953    .0531003
--------------+----------------------------------------------------------------
      sigma_u |  .04747021
      sigma_e |   .0156556
          rho |  .90190279   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est3 stored)

. drop Damaged_2019 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_max if anno == 2019
(166 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_max if anno == 2004
(161 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov if anno > 2009, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,300
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7603                                         min =          2
     Between = 0.6954                                         avg =        2.0
     Overall = 0.5174                                         max =          2

                                                F(7, 51)          =     325.05
corr(u_i, Xb) = 0.2701                          Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.0004676   .0021624    -0.22   0.830    -.0048088    .0038736
              |
         anno |
        2019  |   .0396171   .0021073    18.80   0.000     .0353866    .0438476
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 22  |  -.0186571   .0034267    -5.44   0.000    -.0255364   -.0117778
     2019 24  |  -.0238849   .0023577   -10.13   0.000    -.0286182   -.0191515
     2019 25  |  -.0253499   .0028818    -8.80   0.000    -.0311354   -.0195644
     2019 30  |   -.024536   .0021901   -11.20   0.000    -.0289328   -.0201392
     2019 93  |   -.025824   .0022017   -11.73   0.000     -.030244   -.0214039
              |
        _cons |   .0148534   .0003362    44.18   0.000     .0141784    .0155284
--------------+----------------------------------------------------------------
      sigma_u |  .01494438
      sigma_e |  .00909088
          rho |   .7299025   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est4 stored)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,933
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7207                                         min =          2
     Between = 0.7698                                         avg =        3.0
     Overall = 0.0078                                         max =          3

                                                F(13, 51)         =     576.46
corr(u_i, Xb) = -0.6738                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0006289   .0021088     0.30   0.767    -.0036046    .0048624
              |
         anno |
        2014  |  -.1081598   .0133252    -8.12   0.000    -.1349113   -.0814084
        2019  |   -.068575   .0133778    -5.13   0.000     -.095432   -.0417181
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2014 22  |   .0845435   .0134723     6.28   0.000     .0574967    .1115903
     2014 24  |   .0867788   .0134341     6.46   0.000     .0598087     .113749
     2014 25  |   .0927898     .01335     6.95   0.000     .0659885    .1195911
     2014 30  |   .0947712   .0133562     7.10   0.000     .0679574     .121585
     2014 93  |   .0935682   .0133459     7.01   0.000     .0667752    .1203612
     2019 22  |   .0652945   .0136601     4.78   0.000     .0378708    .0927182
     2019 24  |   .0628782   .0135253     4.65   0.000      .035725    .0900314
     2019 25  |   .0671996   .0134793     4.99   0.000     .0401387    .0942604
     2019 30  |   .0702348   .0134176     5.23   0.000     .0432978    .0971718
     2019 93  |   .0677009   .0134333     5.04   0.000     .0407324    .0946695
              |
        _cons |     .04962   .0016635    29.83   0.000     .0462803    .0529597
--------------+----------------------------------------------------------------
      sigma_u |  .04747539
      sigma_e |  .01565169
          rho |  .90196623   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est5 stored)

. eststo: xtreg party_share Damaged_2019 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,933
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7209                                         min =          2
     Between = 0.7700                                         avg =        3.0
     Overall = 0.0072                                         max =          3

                                                F(14, 51)         =     361.90
corr(u_i, Xb) = -0.6712                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.0004676   .0021644    -0.22   0.830    -.0048128    .0038776
 Damaged_2004 |   -.002237   .0031593    -0.71   0.482    -.0085795    .0041056
              |
         anno |
        2014  |  -.1082152    .013331    -8.12   0.000    -.1349783   -.0814521
        2019  |  -.0685981   .0133793    -5.13   0.000    -.0954582   -.0417379
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2014 22  |   .0833299   .0133118     6.26   0.000     .0566055    .1100544
     2014 24  |   .0867334    .013412     6.47   0.000     .0598077    .1136591
     2014 25  |   .0922747   .0132151     6.98   0.000     .0657443     .118805
     2014 30  |   .0947582   .0133407     7.10   0.000     .0679757    .1215408
     2014 93  |   .0934692   .0133086     7.02   0.000      .066751    .1201875
     2019 22  |   .0646728   .0135474     4.77   0.000     .0374753    .0918703
     2019 24  |   .0628485   .0135169     4.65   0.000     .0357122    .0899849
     2019 25  |   .0669247   .0134436     4.98   0.000     .0399356    .0939139
     2019 30  |   .0702222   .0134104     5.24   0.000     .0432997    .0971448
     2019 93  |   .0676453   .0134153     5.04   0.000     .0407129    .0945776
              |
        _cons |   .0500682    .001885    26.56   0.000     .0462838    .0538526
--------------+----------------------------------------------------------------
      sigma_u |  .04733817
      sigma_e |  .01565466
          rho |  .90141945   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est6 stored)

. drop Damaged_2019 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_binary if anno == 2019
(166 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_binary if anno == 2004
(161 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov if anno > 2009, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,300
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7603                                         min =          2
     Between = 0.6942                                         avg =        2.0
     Overall = 0.5171                                         max =          2

                                                F(7, 51)          =     351.24
corr(u_i, Xb) = 0.2697                          Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0006187   .0020847     0.30   0.768    -.0035664    .0048039
              |
         anno |
        2019  |   .0395767   .0020767    19.06   0.000     .0354074    .0437459
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 22  |   -.019346   .0036819    -5.25   0.000    -.0267378   -.0119543
     2019 24  |   -.023892   .0023431   -10.20   0.000    -.0285961    -.019188
     2019 25  |  -.0255982   .0029818    -8.58   0.000    -.0315843    -.019612
     2019 30  |   -.024528   .0021655   -11.33   0.000    -.0288753   -.0201806
     2019 93  |  -.0258653   .0021747   -11.89   0.000    -.0302311   -.0214995
              |
        _cons |   .0148534   .0003361    44.20   0.000     .0141787    .0155281
--------------+----------------------------------------------------------------
      sigma_u |  .01494821
      sigma_e |  .00909034
          rho |  .73002673   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est7 stored)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,933
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7208                                         min =          2
     Between = 0.7700                                         avg =        3.0
     Overall = 0.0078                                         max =          3

                                                F(13, 51)         =     744.37
corr(u_i, Xb) = -0.6738                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0014904   .0021042     0.71   0.482     -.002734    .0057149
              |
         anno |
        2014  |  -.1081558   .0133258    -8.12   0.000    -.1349085   -.0814031
        2019  |  -.0686167   .0133684    -5.13   0.000    -.0954549   -.0417786
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2014 22  |   .0845398   .0134727     6.27   0.000     .0574921    .1115874
     2014 24  |   .0867741   .0134347     6.46   0.000     .0598029    .1137454
     2014 25  |   .0927814   .0133502     6.95   0.000     .0659799     .119583
     2014 30  |   .0947668   .0133568     7.10   0.000     .0679519    .1215817
     2014 93  |   .0935642   .0133465     7.01   0.000       .06677    .1203585
     2019 22  |   .0645788   .0136304     4.74   0.000     .0372147    .0919429
     2019 24  |   .0628814   .0135121     4.65   0.000     .0357547    .0900082
     2019 25  |   .0669779   .0134596     4.98   0.000     .0399566    .0939993
     2019 30  |   .0702504   .0134044     5.24   0.000     .0433398    .0971609
     2019 93  |   .0676668   .0134155     5.04   0.000      .040734    .0945996
              |
        _cons |   .0496198   .0016637    29.83   0.000     .0462799    .0529598
--------------+----------------------------------------------------------------
      sigma_u |  .04747525
      sigma_e |  .01564973
          rho |  .90198788   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est8 stored)

. eststo: xtreg party_share Damaged_2019 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,933
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7209                                         min =          2
     Between = 0.7705                                         avg =        3.0
     Overall = 0.0073                                         max =          3

                                                F(14, 51)         =     435.70
corr(u_i, Xb) = -0.6713                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0006187   .0020866     0.30   0.768    -.0035704    .0048078
 Damaged_2004 |  -.0017847   .0027203    -0.66   0.515     -.007246    .0036765
              |
         anno |
        2014  |  -.1082219   .0133431    -8.11   0.000    -.1350094   -.0814345
        2019  |  -.0686453   .0133748    -5.13   0.000    -.0954963   -.0417943
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2014 22  |   .0832719   .0131427     6.34   0.000     .0568868     .109657
     2014 24  |   .0867598   .0134175     6.47   0.000      .059823    .1136967
     2014 25  |   .0923374   .0131657     7.01   0.000     .0659062    .1187687
     2014 30  |   .0947784   .0133489     7.10   0.000     .0679793    .1215775
     2014 93  |   .0934876   .0133029     7.03   0.000     .0667809    .1201942
     2019 22  |   .0639259   .0134506     4.75   0.000     .0369227    .0909291
     2019 24  |   .0628678   .0135038     4.66   0.000     .0357578    .0899778
     2019 25  |   .0667393   .0133933     4.98   0.000     .0398511    .0936274
     2019 30  |   .0702504   .0133992     5.24   0.000     .0433503    .0971505
     2019 93  |   .0676223   .0133924     5.05   0.000      .040736    .0945086
              |
        _cons |   .0500746   .0019739    25.37   0.000     .0461117    .0540375
--------------+----------------------------------------------------------------
      sigma_u |  .04734258
      sigma_e |  .01565345
          rho |   .9014497   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est9 stored)

. drop Damaged_2019 Damaged_2004

. 
. esttab using "ax-tab_main_results_green.tex", keep(Damaged_*)  replace b(%8.3f) se(%8.3f) noomitted nobaselev stats(N,  fmt(0 0))  star(+ 0.10 *
>  0.05 ** 0.01 *** 0.001)
(file ax-tab_main_results_green.tex not found)
(output written to ax-tab_main_results_green.tex)

. 
. *************************************************************
. *  Table of Pre-post DID Estimates on Vote for Five Star Movement
. *************************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. keep if party == "M5S" 
(60,624 observations deleted)

. keep if damaged_prov_binary == 1 
(2,336 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. keep if anno == 2014 | anno == 2019
(0 observations deleted)

. 
. xtset pro_com anno

Panel variable: pro_com (strongly balanced)
 Time variable: anno, 2014 to 2019, but with gaps
         Delta: 1 unit

. 
. est clear

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_mean if anno == 2019
(166 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,300
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.8670                                         min =          2
     Between = 0.5139                                         avg =        2.0
     Overall = 0.1947                                         max =          2

                                                F(7, 51)          =     311.36
corr(u_i, Xb) = -0.2887                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.1135025   .0882279    -1.29   0.204    -.2906274    .0636224
              |
         anno |
        2019  |  -.0301252    .003571    -8.44   0.000    -.0372944   -.0229561
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 22  |  -.0227377   .0062571    -3.63   0.001    -.0352994   -.0101761
     2019 24  |  -.0809394   .0057533   -14.07   0.000    -.0924896   -.0693892
     2019 25  |  -.0496566    .007856    -6.32   0.000    -.0654281   -.0338851
     2019 30  |  -.0710473   .0060381   -11.77   0.000    -.0831692   -.0589254
     2019 93  |  -.0739056   .0066307   -11.15   0.000    -.0872174   -.0605939
              |
        _cons |   .1433255   .0009953   144.01   0.000     .1413275    .1453236
--------------+----------------------------------------------------------------
      sigma_u |  .05601169
      sigma_e |  .02281397
          rho |  .85770709   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est1 stored)

. drop Damaged_2019

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_max if anno == 2019
(166 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,300
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.8664                                         min =          2
     Between = 0.5155                                         avg =        2.0
     Overall = 0.1947                                         max =          2

                                                F(7, 51)          =     320.98
corr(u_i, Xb) = -0.2882                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.0022194   .0065795    -0.34   0.737    -.0154284    .0109895
              |
         anno |
        2019  |  -.0300904   .0035762    -8.41   0.000      -.03727   -.0229109
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 22  |  -.0237358   .0069554    -3.41   0.001    -.0376994   -.0097723
     2019 24  |  -.0810755   .0057704   -14.05   0.000      -.09266    -.069491
     2019 25  |  -.0499028   .0082512    -6.05   0.000    -.0664677   -.0333378
     2019 30  |  -.0711672   .0060041   -11.85   0.000    -.0832209   -.0591135
     2019 93  |  -.0738219   .0064247   -11.49   0.000      -.08672   -.0609238
              |
        _cons |   .1433255   .0010275   139.49   0.000     .1412628    .1453883
--------------+----------------------------------------------------------------
      sigma_u |  .05599034
      sigma_e |   .0228693
          rho |  .85702137   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est2 stored)

. drop Damaged_2019

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_binary if anno == 2019
(166 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,300
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.8664                                         min =          2
     Between = 0.5153                                         avg =        2.0
     Overall = 0.1948                                         max =          2

                                                F(7, 51)          =     335.71
corr(u_i, Xb) = -0.2882                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.0021519   .0052776    -0.41   0.685    -.0127472    .0084434
              |
         anno |
        2019  |  -.0300631   .0035708    -8.42   0.000    -.0372319   -.0228944
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 22  |  -.0234157   .0063369    -3.70   0.001    -.0361376   -.0106938
     2019 24  |  -.0811058   .0057614   -14.08   0.000    -.0926722   -.0695394
     2019 25  |  -.0498823   .0082459    -6.05   0.000    -.0664365    -.033328
     2019 30  |  -.0711965   .0060094   -11.85   0.000    -.0832609   -.0591322
     2019 93  |  -.0738302   .0064172   -11.51   0.000    -.0867132   -.0609472
              |
        _cons |   .1433255   .0010296   139.20   0.000     .1412584    .1453926
--------------+----------------------------------------------------------------
      sigma_u |  .05598884
      sigma_e |  .02286873
          rho |  .85702091   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est3 stored)

. drop Damaged_2019

. 
. esttab using "ax-tab_main_results_m5s.tex", keep(Damaged_*)  replace b(%8.3f) se(%8.3f) noomitted nobaselev stats(N,  fmt(0 0))  star(+ 0.10 * 0
> .05 ** 0.01 *** 0.001)
(file ax-tab_main_results_m5s.tex not found)
(output written to ax-tab_main_results_m5s.tex)

. 
. **************************************************************
. * Table of Pre-post DID Estimates on Vote for Mainstream Parties
. **************************************************************
. 
. * Forza Italia
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if party == "FI" 
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. est clear

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_mean if anno == 2019
(166 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_mean if anno == 2009
(164 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_mean if anno == 2004
(161 real changes made)

. eststo:     xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.8917                                         min =          2
     Between = 0.3426                                         avg =        4.0
     Overall = 0.3246                                         max =          4

                                                F(21, 51)         =    5152.10
corr(u_i, Xb) = -0.2525                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0000667    .110999     0.00   1.000    -.2227732    .2229065
 Damaged_2009 |   -.028763   .1891563    -0.15   0.880      -.40851    .3509841
 Damaged_2004 |   .0598272   .1702037     0.35   0.727     -.281871    .4015254
              |
         anno |
        2009  |   .0211596   .0033033     6.41   0.000      .014528    .0277913
        2014  |  -.0103293   .0022675    -4.56   0.000    -.0148814   -.0057772
        2019  |  -.0197437   .0038472    -5.13   0.000    -.0274673   -.0120201
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0184515    .006746     2.74   0.009     .0049084    .0319946
     2009 24  |   .0051333   .0081229     0.63   0.530    -.0111741    .0214407
     2009 25  |   .0140613   .0104226     1.35   0.183    -.0068631    .0349856
     2009 30  |   .0628231   .0046134    13.62   0.000     .0535614    .0720848
     2009 93  |   .0315454   .0061837     5.10   0.000     .0191311    .0439596
     2014 22  |    -.11877   .0070529   -16.84   0.000    -.1329293   -.1046107
     2014 24  |   -.109825   .0087021   -12.62   0.000    -.1272952   -.0923548
     2014 25  |  -.1082044   .0082968   -13.04   0.000    -.1248609   -.0915479
     2014 30  |  -.0644901   .0034758   -18.55   0.000    -.0714681   -.0575122
     2014 93  |  -.0970693   .0188325    -5.15   0.000    -.1348772   -.0592614
     2019 22  |  -.1585523    .008805   -18.01   0.000    -.1762291   -.1408755
     2019 24  |  -.1867619   .0112634   -16.58   0.000    -.2093741   -.1641498
     2019 25  |  -.1705576   .0140475   -12.14   0.000    -.1987593    -.142356
     2019 30  |  -.1312639   .0084609   -15.51   0.000    -.1482498    -.114278
     2019 93  |  -.1695556   .0145921   -11.62   0.000    -.1988504   -.1402607
              |
        _cons |   .1995279   .0020726    96.27   0.000     .1953669    .2036888
--------------+----------------------------------------------------------------
      sigma_u |  .09007529
      sigma_e |  .03323528
          rho |  .88017284   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est1 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_max if anno == 2019
(166 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_max if anno == 2009
(164 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_max if anno == 2004
(161 real changes made)

. eststo:     xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.8917                                         min =          2
     Between = 0.3388                                         avg =        4.0
     Overall = 0.3217                                         max =          4

                                                F(21, 51)         =    5455.98
corr(u_i, Xb) = -0.2566                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.0012129    .009407    -0.13   0.898    -.0200983    .0176725
 Damaged_2009 |  -.0043846   .0117323    -0.37   0.710    -.0279381    .0191689
 Damaged_2004 |  -.0024344   .0107271    -0.23   0.821    -.0239699    .0191011
              |
         anno |
        2009  |   .0211978   .0033337     6.36   0.000      .014505    .0278906
        2014  |  -.0104127   .0023439    -4.44   0.000    -.0151182   -.0057072
        2019  |  -.0197913   .0039142    -5.06   0.000    -.0276494   -.0119332
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0177428   .0075844     2.34   0.023     .0025165    .0329692
     2009 24  |   .0050224   .0081881     0.61   0.542     -.011416    .0214608
     2009 25  |   .0139086   .0103059     1.35   0.183    -.0067814    .0345985
     2009 30  |    .062722   .0046139    13.59   0.000     .0534593    .0719848
     2009 93  |   .0316148    .006215     5.09   0.000     .0191376    .0440919
     2014 22  |  -.1212674   .0090817   -13.35   0.000    -.1394998   -.1030351
     2014 24  |  -.1099595   .0086982   -12.64   0.000    -.1274219    -.092497
     2014 25  |  -.1091578   .0089537   -12.19   0.000    -.1271331   -.0911825
     2014 30  |  -.0645627   .0034834   -18.53   0.000     -.071556   -.0575694
     2014 93  |  -.0971721   .0188415    -5.16   0.000     -.134998   -.0593462
     2019 22  |  -.1603938   .0094388   -16.99   0.000     -.179343   -.1414445
     2019 24  |  -.1868789   .0112962   -16.54   0.000     -.209557   -.1642007
     2019 25  |  -.1712448    .014583   -11.74   0.000    -.2005214   -.1419681
     2019 30  |   -.131336   .0084349   -15.57   0.000    -.1482698   -.1144021
     2019 93  |  -.1696105   .0146215   -11.60   0.000    -.1989643   -.1402566
              |
        _cons |   .2004182   .0028328    70.75   0.000     .1947311    .2061053
--------------+----------------------------------------------------------------
      sigma_u |  .09038913
      sigma_e |  .03323994
          rho |  .88087515   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est2 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_binary if anno == 2019
(166 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_binary if anno == 2009
(164 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_binary if anno == 2004
(161 real changes made)

. eststo:     xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.8916                                         min =          2
     Between = 0.3394                                         avg =        4.0
     Overall = 0.3222                                         max =          4

                                                F(21, 51)         =    5925.92
corr(u_i, Xb) = -0.2559                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |  -.0001824      .0082    -0.02   0.982    -.0166446    .0162797
 Damaged_2009 |  -.0024672   .0090458    -0.27   0.786    -.0206274    .0156929
 Damaged_2004 |    -.00133     .00884    -0.15   0.881     -.019077     .016417
              |
         anno |
        2009  |   .0211893   .0033454     6.33   0.000     .0144731    .0279055
        2014  |  -.0103982    .002353    -4.42   0.000     -.015122   -.0056745
        2019  |  -.0198048   .0039525    -5.01   0.000    -.0277398   -.0118698
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0174981   .0085079     2.06   0.045     .0004177    .0345784
     2009 24  |   .0049943   .0081862     0.61   0.545    -.0114403    .0214288
     2009 25  |   .0137433   .0103592     1.33   0.191    -.0070537    .0345402
     2009 30  |   .0627061   .0046126    13.59   0.000     .0534459    .0719664
     2009 93  |   .0315796   .0062177     5.08   0.000     .0190971    .0440622
     2014 22  |  -.1208958    .009419   -12.84   0.000    -.1398052   -.1019864
     2014 24  |  -.1099248   .0087037   -12.63   0.000    -.1273982   -.0924513
     2014 25  |  -.1089338   .0087848   -12.40   0.000    -.1265701   -.0912975
     2014 30  |   -.064544   .0034887   -18.50   0.000    -.0715479   -.0575402
     2014 93  |   -.097125   .0188509    -5.15   0.000    -.1349697   -.0592804
     2019 22  |  -.1605481   .0096691   -16.60   0.000    -.1799597   -.1411365
     2019 24  |  -.1868614   .0112864   -16.56   0.000    -.2095198   -.1642031
     2019 25  |  -.1712437   .0145457   -11.77   0.000    -.2004454   -.1420419
     2019 30  |  -.1313201    .008465   -15.51   0.000    -.1483144   -.1143259
     2019 93  |  -.1696046   .0146137   -11.61   0.000    -.1989427   -.1402664
              |
        _cons |   .2002694   .0029343    68.25   0.000     .1943786    .2061602
--------------+----------------------------------------------------------------
      sigma_u |  .09033424
      sigma_e |  .03324227
          rho |  .88073287   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est3 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. * PD
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if party == "PD" 
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_mean if anno == 2019
(166 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_mean if anno == 2009
(164 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_mean if anno == 2004
(161 real changes made)

. eststo:     xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7786                                         min =          2
     Between = 0.0116                                         avg =        4.0
     Overall = 0.2218                                         max =          4

                                                F(21, 51)         =    3869.52
corr(u_i, Xb) = -0.1608                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   -.175961   .1110991    -1.58   0.119    -.3990017    .0470797
 Damaged_2009 |  -.1620548    .106157    -1.53   0.133    -.3751739    .0510643
 Damaged_2004 |   .2410138   .1441974     1.67   0.101    -.0484745    .5305021
              |
         anno |
        2009  |  -.0412164   .0059261    -6.96   0.000    -.0531135   -.0293194
        2014  |  -.0099736   .0048381    -2.06   0.044    -.0196865   -.0002606
        2019  |  -.0449461   .0064566    -6.96   0.000    -.0579083    -.031984
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |  -.0862187   .0103779    -8.31   0.000    -.1070532   -.0653843
     2009 24  |  -.0310229   .0066299    -4.68   0.000     -.044333   -.0177127
     2009 25  |  -.0286832   .0091362    -3.14   0.003    -.0470249   -.0103414
     2009 30  |   .0112869   .0064343     1.75   0.085    -.0016305    .0242043
     2009 93  |   .0152351   .0088609     1.72   0.092    -.0025539    .0330241
     2014 22  |  -.0016158   .0126066    -0.13   0.899    -.0269245    .0236929
     2014 24  |    .125768   .0073758    17.05   0.000     .1109605    .1405756
     2014 25  |   .1094028   .0112789     9.70   0.000     .0867595    .1320461
     2014 30  |   .1504656   .0120585    12.48   0.000     .1262571     .174674
     2014 93  |   .1480375    .012206    12.13   0.000     .1235328    .1725421
     2019 22  |  -.1128501   .0106906   -10.56   0.000    -.1343123   -.0913879
     2019 24  |  -.0319759   .0095909    -3.33   0.002    -.0512305   -.0127214
     2019 25  |   -.056179   .0168861    -3.33   0.002    -.0900793   -.0222788
     2019 30  |  -.0472154   .0100222    -4.71   0.000    -.0673359    -.027095
     2019 93  |  -.0228585   .0104192    -2.19   0.033     -.043776    -.001941
              |
        _cons |   .2503047   .0023776   105.27   0.000     .2455314     .255078
--------------+----------------------------------------------------------------
      sigma_u |  .10859341
      sigma_e |  .04429039
          rho |  .85737861   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est4 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_max if anno == 2019
(166 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_max if anno == 2009
(164 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_max if anno == 2004
(161 real changes made)

. eststo:     xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7825                                         min =          2
     Between = 0.0002                                         avg =        4.0
     Overall = 0.2822                                         max =          4

                                                F(21, 51)         =    3756.96
corr(u_i, Xb) = -0.0651                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |    .003689   .0108565     0.34   0.735    -.0181062    .0254843
 Damaged_2009 |   .0138187   .0147003     0.94   0.352    -.0156935    .0433309
 Damaged_2004 |   .0548711   .0153163     3.58   0.001     .0241223      .08562
              |
         anno |
        2009  |  -.0404174   .0055196    -7.32   0.000    -.0514985   -.0293363
        2014  |  -.0087233   .0047762    -1.83   0.074    -.0183119    .0008652
        2019  |  -.0438521   .0058527    -7.49   0.000     -.055602   -.0321023
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |  -.0718126   .0097164    -7.39   0.000     -.091319   -.0523061
     2009 24  |  -.0306829   .0064205    -4.78   0.000    -.0435726   -.0177931
     2009 25  |  -.0217296   .0073813    -2.94   0.005    -.0365482    -.006911
     2009 30  |   .0112041   .0060655     1.85   0.071    -.0009728     .023381
     2009 93  |   .0171458   .0098703     1.74   0.088    -.0026697    .0369613
     2014 22  |   .0233443   .0111123     2.10   0.041     .0010354    .0456531
     2014 24  |   .1265642   .0078716    16.08   0.000     .1107614     .142367
     2014 25  |   .1205492   .0074312    16.22   0.000     .1056306    .1354679
     2014 30  |   .1505636   .0125486    12.00   0.000     .1253713    .1757558
     2014 93  |   .1504998   .0095245    15.80   0.000     .1313786    .1696211
     2019 22  |  -.0932858   .0092227   -10.11   0.000    -.1118012   -.0747704
     2019 24  |  -.0314932   .0093019    -3.39   0.001    -.0501676   -.0128188
     2019 25  |  -.0469771   .0121467    -3.87   0.000    -.0713626   -.0225916
     2019 30  |  -.0473059   .0092882    -5.09   0.000    -.0659528    -.028659
     2019 93  |   -.020548   .0077361    -2.66   0.011    -.0360788   -.0050171
              |
        _cons |   .2409432   .0025883    93.09   0.000     .2357471    .2461393
--------------+----------------------------------------------------------------
      sigma_u |  .10271765
      sigma_e |  .04390007
          rho |  .84555248   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est5 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_binary if anno == 2019
(166 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_binary if anno == 2009
(164 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_binary if anno == 2004
(161 real changes made)

. eststo:     xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.7806                                         min =          2
     Between = 0.0000                                         avg =        4.0
     Overall = 0.2795                                         max =          4

                                                F(21, 51)         =    3958.79
corr(u_i, Xb) = -0.0672                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |    .000679    .015473     0.04   0.965    -.0303842    .0317423
 Damaged_2009 |   .0110808   .0170587     0.65   0.519    -.0231659    .0453275
 Damaged_2004 |   .0400079   .0160451     2.49   0.016     .0077961    .0722197
              |
         anno |
        2009  |  -.0403626   .0055446    -7.28   0.000    -.0514939   -.0292313
        2014  |  -.0085984   .0048293    -1.78   0.081    -.0182937    .0010969
        2019  |  -.0436477   .0058287    -7.49   0.000    -.0553493    -.031946
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |  -.0735206   .0095756    -7.68   0.000    -.0927444   -.0542967
     2009 24  |  -.0312892   .0063235    -4.95   0.000    -.0439841   -.0185943
     2009 25  |  -.0240046   .0073178    -3.28   0.002    -.0386956   -.0093135
     2009 30  |   .0107756   .0060585     1.78   0.081    -.0013873    .0229385
     2009 93  |   .0165726   .0095951     1.73   0.090    -.0026905    .0358356
     2014 22  |    .022016   .0145511     1.51   0.136    -.0071965    .0512286
     2014 24  |   .1257662   .0077115    16.31   0.000     .1102848    .1412477
     2014 25  |   .1178563   .0082878    14.22   0.000     .1012179    .1344947
     2014 30  |   .1499829   .0124079    12.09   0.000     .1250731    .1748928
     2014 93  |   .1497894   .0099495    15.05   0.000      .129815    .1697639
     2019 22  |  -.0931018   .0092792   -10.03   0.000    -.1117306   -.0744731
     2019 24  |  -.0322387   .0091806    -3.51   0.001    -.0506695   -.0138079
     2019 25  |  -.0490214   .0125099    -3.92   0.000     -.074136   -.0239067
     2019 30  |  -.0478762   .0093674    -5.11   0.000    -.0666821   -.0290703
     2019 93  |  -.0211377   .0079059    -2.67   0.010    -.0370095   -.0052659
              |
        _cons |   .2417407   .0037062    65.23   0.000     .2343002    .2491812
--------------+----------------------------------------------------------------
      sigma_u |  .10289378
      sigma_e |  .04409323
          rho |  .84485202   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est6 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. esttab using "ax-tab_did_pd_fi.tex", keep(Damaged_*)  replace b(%8.3f) se(%8.3f) noomitted nobaselev stats(N,  fmt(0 0))  star(+ 0.10 * 0.05 ** 
> 0.01 *** 0.001)
(file ax-tab_did_pd_fi.tex not found)
(output written to ax-tab_did_pd_fi.tex)

. 
. 
. ***************************************************************
. * Plot of Trends in Raw Means of Vote Share by Treatment Group
. ***************************************************************
. 
. * Incumbent
. use "vaia.dta", clear
(Written by R.              )

. 
. keep if anno == 2004 | anno == 2009 | anno == 2014 | anno == 2019
(2,536 observations deleted)

. keep if tipo_elezione == "europea"
(0 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22)) | (party == "SVP" & cod_prov == 21)
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. 
. collapse (mean) party_share (semean) se=party_share, by(anno damage_binary)

. 
. gen per = party_share*100

. gen cilo = per-1.96 * se*100

. gen cihi = per+1.96 * se*100

. 
. rename anno year

. rename damage_binary damaged

. 
. keep year damaged per cilo cihi

. 
. save "parallel_incumbent_damage.dta", replace
(file parallel_incumbent_damage.dta not found)
file parallel_incumbent_damage.dta saved

. 
. 
. * Green
. use "vaia.dta", clear
(Written by R.              )

. 
. keep if anno == 2004 | anno == 2014 | anno == 2019 
(11,008 observations deleted)

. keep if tipo_elezione == "europea"
(0 observations deleted)

. keep if party == "green" 
(48,566 observations deleted)

. keep if damaged_prov_binary == 1 
(2,753 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. 
. collapse (mean) party_share (semean) se=party_share, by(anno damage_binary)

. 
. gen per = party_share*100

. gen cilo = per-1.96 * se*100

. gen cihi = per+1.96 * se*100

. 
. rename anno year

. rename damage_binary damaged

. 
. keep year damaged per cilo cihi

. 
. save "parallel_green_damage.dta", replace
(file parallel_green_damage.dta not found)
file parallel_green_damage.dta saved

. 
. * M5S
. use "vaia.dta", clear
(Written by R.              )

. 
. keep if anno == 2014 | anno == 2019
(19,408 observations deleted)

. keep if tipo_elezione == "europea"
(0 observations deleted)

. keep if party == "M5S" 
(41,216 observations deleted)

. keep if damaged_prov_binary == 1 
(2,336 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. 
. collapse (mean) party_share (semean) se=party_share, by(anno damage_binary)

. 
. gen per = party_share*100

. gen cilo = per-1.96 * se*100

. gen cihi = per+1.96 * se*100

. 
. rename anno year

. rename damage_binary damaged

. 
. keep year damaged per cilo cihi

. 
. save "parallel_m5s_damage.dta", replace
(file parallel_m5s_damage.dta not found)
file parallel_m5s_damage.dta saved

. 
. 
. ******************************************************
. * Table of Dose Response Estimates 
. ******************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. 
. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22)) | (party == "SVP" & cod_prov == 21)
(55,979 observations deleted)

. 
. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. 
. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. xtile damage_mean_tiles_t = damage_mean if anno == 2019 & damage_binary == 1, n(3)

. xtile damage_max_tiles_t = damage_max if anno == 2019 & damage_binary == 1, n(3)

. 
. replace damage_mean_tiles_t = 0 if anno != 2019 | damage_binary != 1
(2,409 real changes made)

. replace damage_max_tiles_t = 0 if anno != 2019  | damage_binary != 1
(2,409 real changes made)

.  
. est clear

. 
. rename damage_mean_tiles_t Damaged_t

. eststo: xtreg party_share i.Damaged_t  i.anno##i.cod_prov, fe cl(SLL_2011)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9589                                         min =          2
     Between = 0.6447                                         avg =        4.0
     Overall = 0.1719                                         max =          4

                                                F(21, 51)         =    2058.50
corr(u_i, Xb) = -0.2429                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
    Damaged_t |
           1  |   .0119059   .0081609     1.46   0.151    -.0044778    .0282895
           2  |   .0353565   .0095966     3.68   0.001     .0160906    .0546225
           3  |   .0296894   .0102886     2.89   0.006     .0090341    .0503447
              |
         anno |
        2009  |   .0696559   .0055248    12.61   0.000     .0585643    .0807475
        2014  |   .0326788   .0064544     5.06   0.000      .019721    .0456365
        2019  |  -.0192477   .0066186    -2.91   0.005    -.0325351   -.0059604
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0330465   .0076215     4.34   0.000     .0177458    .0483472
     2009 24  |   .1006693   .0088444    11.38   0.000     .0829135    .1184252
     2009 25  |    .057017   .0087135     6.54   0.000     .0395239    .0745101
     2009 30  |   .0248281   .0069082     3.59   0.001     .0109594    .0386969
     2009 93  |   .0448847   .0082717     5.43   0.000     .0282784    .0614909
     2014 22  |  -.0219782   .0088344    -2.49   0.016     -.039714   -.0042425
     2014 24  |  -.0380501   .0084773    -4.49   0.000     -.055069   -.0210313
     2014 25  |  -.0780537   .0093185    -8.38   0.000    -.0967614   -.0593459
     2014 30  |  -.0280554   .0070025    -4.01   0.000    -.0421135   -.0139972
     2014 93  |  -.0488889    .007306    -6.69   0.000    -.0635562   -.0342215
     2019 22  |   .3612895     .01284    28.14   0.000     .3355121    .3870668
     2019 24  |   .3886198   .0095589    40.66   0.000     .3694296    .4078101
     2019 25  |   .3331377   .0109226    30.50   0.000     .3112097    .3550656
     2019 30  |   .4058093    .011724    34.61   0.000     .3822723    .4293463
     2019 93  |    .376938   .0107198    35.16   0.000     .3554171    .3984589
              |
        _cons |   .2176376   .0016143   134.82   0.000     .2143967    .2208785
--------------+----------------------------------------------------------------
      sigma_u |  .20742562
      sigma_e |  .03309866
          rho |  .97517001   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est1 stored)

. rename Damaged_t damage_mean_tiles_t 

. 
. rename damage_max_tiles_t Damaged_t

. eststo: xtreg party_share i.Damaged_t  i.anno##i.cod_prov, fe cl(SLL_2011)
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,575
Group variable: pro_com                         Number of groups  =        650

R-squared:                                      Obs per group:
     Within  = 0.9590                                         min =          2
     Between = 0.6450                                         avg =        4.0
     Overall = 0.1720                                         max =          4

                                                F(21, 51)         =    2142.93
corr(u_i, Xb) = -0.2427                         Prob > F          =     0.0000

                               (Std. err. adjusted for 52 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
    Damaged_t |
           1  |   .0066183   .0119487     0.55   0.582    -.0173697    .0306064
           2  |    .028587   .0078656     3.63   0.001     .0127962    .0443779
           3  |   .0464527   .0137133     3.39   0.001     .0189221    .0739833
              |
         anno |
        2009  |   .0697036    .005509    12.65   0.000     .0586438    .0807633
        2014  |   .0327265   .0064491     5.07   0.000     .0197794    .0456735
        2019  |   -.019387   .0066301    -2.92   0.005    -.0326975   -.0060765
              |
     cod_prov |
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 22  |   .0329148   .0076042     4.33   0.000     .0176488    .0481808
     2009 24  |   .1006198   .0088341    11.39   0.000     .0828845    .1183551
     2009 25  |   .0569693   .0087051     6.54   0.000     .0394931    .0744455
     2009 30  |   .0247769   .0068953     3.59   0.001     .0109339    .0386199
     2009 93  |    .044837   .0082607     5.43   0.000     .0282529    .0614211
     2014 22  |  -.0221207   .0088313    -2.50   0.015    -.0398502   -.0043912
     2014 24  |  -.0381076   .0084704    -4.50   0.000    -.0551127   -.0211024
     2014 25  |  -.0781134   .0093118    -8.39   0.000    -.0968077   -.0594191
     2014 30  |  -.0281083   .0069968    -4.02   0.000    -.0421549   -.0140617
     2014 93  |  -.0489366   .0073005    -6.70   0.000     -.063593   -.0342801
     2019 22  |   .3662313   .0135622    27.00   0.000     .3390042    .3934585
     2019 24  |   .3881632   .0095571    40.61   0.000     .3689765      .40735
     2019 25  |   .3325519   .0105721    31.46   0.000     .3113275    .3537763
     2019 30  |   .4054851    .011719    34.60   0.000     .3819583     .429012
     2019 93  |   .3762118   .0104012    36.17   0.000     .3553306     .397093
              |
        _cons |   .2176519   .0015937   136.57   0.000     .2144525    .2208514
--------------+----------------------------------------------------------------
      sigma_u |  .20738729
      sigma_e |  .03306169
          rho |  .97521516   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est2 stored)

. rename Damaged_t damage_max_tiles_t 

. 
. esttab using "ax-tab_dose_response.tex", keep(*.Damaged_*)  replace b(%8.3f) se(%8.3f) noomitted nobaselev stats(N,  fmt(0 0))  star(+ 0.10 * 0.
> 05 ** 0.01 *** 0.001)
(file ax-tab_dose_response.tex not found)
(output written to ax-tab_dose_response.tex)

. 
. 
. ***************************************************************
. * Table of Covariate Balance Before and After IPW
. ***************************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22)) | (party == "SVP" & cod_prov == 21)
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. keep if anno == 2019
(1,925 observations deleted)

. 
. gen logalt = log(mean_altitude+1)

. 
. logit damage_binary logalt income_ind_2017 pop_tot_1jan18 forest_perc pop_dens18 foreign_share_1jan18 if anno == 2019 

Iteration 0:  Log likelihood = -363.15298  
Iteration 1:  Log likelihood = -295.65193  
Iteration 2:  Log likelihood = -274.35475  
Iteration 3:  Log likelihood = -267.76439  
Iteration 4:  Log likelihood = -267.49943  
Iteration 5:  Log likelihood = -267.49866  
Iteration 6:  Log likelihood = -267.49866  

Logistic regression                                     Number of obs =    640
                                                        LR chi2(6)    = 191.31
                                                        Prob > chi2   = 0.0000
Log likelihood = -267.49866                             Pseudo R2     = 0.2634

--------------------------------------------------------------------------------------
       damage_binary | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
---------------------+----------------------------------------------------------------
              logalt |   2.242553   .3488311     6.43   0.000     1.558857     2.92625
     income_ind_2017 |  -.0001149   .0000471    -2.44   0.015    -.0002073   -.0000226
      pop_tot_1jan18 |  -5.49e-07   .0000207    -0.03   0.979    -.0000412    .0000401
         forest_perc |   3.115918   .7508253     4.15   0.000     1.644327    4.587508
          pop_dens18 |   .0021676   .0012967     1.67   0.095    -.0003739    .0047091
foreign_share_1jan18 |   1.024546   3.286135     0.31   0.755    -5.416159    7.465251
               _cons |  -16.44821   2.812171    -5.85   0.000    -21.95997   -10.93646
--------------------------------------------------------------------------------------

. predict pscore
(option pr assumed; Pr(damage_binary))
(10 missing values generated)

. 
. * Gen IPW
. sum pscore if damage_binary == 1 & anno == 2019

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      pscore |        163    .4360966    .1328475   .0341655   .7150978

. sum pscore if damage_binary == 0 & anno == 2019

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      pscore |        477    .1926966    .2015376   8.66e-08   .7846277

. gen support = 0 if anno == 2019

. replace support = 1 if pscore >= .0341655 & pscore <= .7150978
(442 real changes made)

. gen w_IPW = .
(650 missing values generated)

. replace w_IPW = 1/pscore if damage_binary == 1 & anno == 2019
(163 real changes made)

. replace w_IPW = 1/(1-pscore) if damage_binary == 0 & support == 1 & anno == 2019
(279 real changes made)

. bys pro_com: egen _ipw  = max(w_IPW)
(208 missing values generated)

. drop w_IPW

. 
. rename damage_binary treated

. 
. * Balance table
. matrix table = J(6, 10, .) 

. 
. local i = 1

. foreach var of varlist logalt income_ind_2017 pop_tot_1jan18 forest_perc pop_dens18 foreign_share_1jan18 {
  2. 
.     summarize `var' if treated == 0
  3.     matrix table[`i', 1] = r(mean)
  4.     matrix table[`i', 2] = r(sd)
  5. 
.     summarize `var' if treated == 1
  6.     matrix table[`i', 3] = r(mean)
  7.     matrix table[`i', 4] = r(sd)
  8. 
.     quietly reg `var' treated
  9.     matrix table[`i', 5] = _b[treated]
 10. 
. 
.     local t = _b[treated] / _se[treated]
 11.     local p = 2 * ttail(e(df_r), abs(`t'))
 12.     matrix table[`i', 6] = `t'
 13.     matrix table[`i', 7] = `p'
 14. 
.     quietly reg `var' treated [aw = _ipw]
 15.     matrix table[`i', 8] = _b[treated]
 16. 
.     local t_w = _b[treated] / _se[treated]
 17.     local p_w = 2 * ttail(e(df_r), abs(`t_w'))
 18.     matrix table[`i', 9] = `t_w'
 19.     matrix table[`i', 10] = `p_w'
 20. 
.     local i = `i' + 1
 21. }

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      logalt |        484    5.789353    1.598759   .8932145    7.82209

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      logalt |        166    7.149874     .339521    5.88266   7.767316

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
income_~2017 |        477    19262.26    2466.043   11399.45   26458.23

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
income_~2017 |        163    18356.91    1892.908   13251.41   24083.67

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
pop_tot_1~18 |        484    5154.539    9948.961        115     110756

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
pop_tot_1~18 |        166    2861.892    9516.424        137     119004

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 forest_perc |        484    .4236037    .2796274          0   .9533306

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 forest_perc |        166     .642018     .138373    .273284   .9469121

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  pop_dens18 |        484    188.6972    247.7661    2.37317   2048.021

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  pop_dens18 |        166    69.95292    93.62664   2.465912   753.7623

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
foreign_s~18 |        484    .0631019    .0349556   .0029155    .251992

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
foreign_s~18 |        166    .0538094    .0307445          0   .1738636

. 
. * Sample stats
. summarize logalt income_ind_2017 pop_tot_1jan18 forest_perc pop_dens18 foreign_share_1jan18 

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      logalt |        650    6.136809    1.511324   .8932145    7.82209
income_~2017 |        640    19031.68    2365.232   11399.45   26458.23
pop_tot_1~18 |        650    4569.032    9883.817        115     119004
 forest_perc |        650    .4793834    .2685989          0   .9533306
  pop_dens18 |        650    158.3717    224.9454    2.37317   2048.021
-------------+---------------------------------------------------------
foreign_s~18 |        650    .0607287    .0341484          0    .251992

. matrix table[6, 1] = r(mean)

. matrix table[6, 2] = r(sd)

. 
. * Set number format
. forval j = 1/6 {
  2.     forval k = 1/10 {
  3.         matrix table[`j', `k'] = round(table[`j', `k'], 0.01)
  4.     }
  5. }

. 
. * Set column names
. matrix colnames table = Mean_Group0 SD_Group0 Mean_Group1 SD_Group1 Coeff_NoWeights Tstat_NoWeights P-Value_NoWeights Coeff_Weights Tstat_Weight
> s P-Value_Weights

. matrix rownames table = logalt income_ind_2017 pop_tot_1jan18 forest_perc pop_dens18 foreign_share_1jan18 

. 
. * Export
. label var pop_tot_1jan18 "Population (2018)"

. label var foreign_share_1jan18 "Foreigners (\%, 2018)"

. label var income_ind_2017 "Average Income (2017)"

. label var logalt "Mean Altitude (log)"

. label var forest_perc "Forest area (\%, 2010)"

. label var pop_dens18 "Population density (2018)"

. 
. estout matrix(table) using "ax-tab_balance.tex", replace style(tex) label cells(fmt(%9.2fc))
(file ax-tab_balance.tex not found)
(output written to ax-tab_balance.tex)

. 
. *****************************************************************
. * Table of Pre-Post DID Estimates Aggregating by Labor Market Area
. *****************************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22))  | (party == "SVP" & cod_prov == 21)
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. 
. collapse (mean) party_share damage_mean_t damage_max_t  (max) damage_binary_t, by(SLL_2011 anno)

. 
. xtset SLL_2011 anno

Panel variable: SLL_2011 (strongly balanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. est clear

. 
. gen Damaged_2019 = damage_mean_t

. eststo: xtreg party_share Damaged_2019 i.anno, fe cl(SLL)

Fixed-effects (within) regression               Number of obs     =        208
Group variable: SLL_2011                        Number of groups  =         52

R-squared:                                      Obs per group:
     Within  = 0.7206                                         min =          4
     Between = 0.0770                                         avg =        4.0
     Overall = 0.2425                                         max =          4

                                                F(4, 51)          =     118.97
corr(u_i, Xb) = -0.0318                         Prob > F          =     0.0000

                              (Std. err. adjusted for 52 clusters in SLL_2011)
------------------------------------------------------------------------------
             |               Robust
 party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
Damaged_2019 |   3.195518   .9983578     3.20   0.002     1.191231    5.199805
             |
        anno |
       2009  |   .1135086    .006108    18.58   0.000     .1012462     .125771
       2014  |   .0026413   .0041821     0.63   0.530    -.0057546    .0110372
       2019  |   .2566256   .0269616     9.52   0.000     .2024979    .3107533
             |
       _cons |   .2479078   .0064475    38.45   0.000     .2349639    .2608516
-------------+----------------------------------------------------------------
     sigma_u |  .18174462
     sigma_e |  .08356327
         rho |  .82549026   (fraction of variance due to u_i)
------------------------------------------------------------------------------
(est1 stored)

. drop Damaged_2019

. 
. gen Damaged_2019 = damage_max_t

. eststo: xtreg party_share Damaged_2019 i.anno, fe cl(SLL)

Fixed-effects (within) regression               Number of obs     =        208
Group variable: SLL_2011                        Number of groups  =         52

R-squared:                                      Obs per group:
     Within  = 0.7403                                         min =          4
     Between = 0.1760                                         avg =        4.0
     Overall = 0.2248                                         max =          4

                                                F(4, 51)          =     325.67
corr(u_i, Xb) = -0.0645                         Prob > F          =     0.0000

                              (Std. err. adjusted for 52 clusters in SLL_2011)
------------------------------------------------------------------------------
             |               Robust
 party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
Damaged_2019 |   .1884511   .0431215     4.37   0.000     .1018812     .275021
             |
        anno |
       2009  |   .1135086    .006108    18.58   0.000     .1012462     .125771
       2014  |   .0026413   .0041821     0.63   0.530    -.0057546    .0110372
       2019  |   .2337188   .0311421     7.50   0.000     .1711984    .2962392
             |
       _cons |   .2479078    .006267    39.56   0.000     .2353262    .2604894
-------------+----------------------------------------------------------------
     sigma_u |  .18547503
     sigma_e |  .08055571
         rho |  .84130132   (fraction of variance due to u_i)
------------------------------------------------------------------------------
(est2 stored)

. drop Damaged_2019

. 
. gen Damaged_2019 = damage_binary_t

. eststo: xtreg party_share Damaged_2019 i.anno, fe cl(SLL)

Fixed-effects (within) regression               Number of obs     =        208
Group variable: SLL_2011                        Number of groups  =         52

R-squared:                                      Obs per group:
     Within  = 0.7206                                         min =          4
     Between = 0.1411                                         avg =        4.0
     Overall = 0.2353                                         max =          4

                                                F(4, 51)          =      96.11
corr(u_i, Xb) = -0.0407                         Prob > F          =     0.0000

                              (Std. err. adjusted for 52 clusters in SLL_2011)
------------------------------------------------------------------------------
             |               Robust
 party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
Damaged_2019 |   .0881133   .0433002     2.03   0.047     .0011844    .1750421
             |
        anno |
       2009  |   .1135086    .006108    18.58   0.000     .1012462     .125771
       2014  |   .0026413   .0041821     0.63   0.530    -.0057546    .0110372
       2019  |   .2369283   .0350275     6.76   0.000     .1666076     .307249
             |
       _cons |   .2479078   .0065714    37.73   0.000     .2347152    .2611003
-------------+----------------------------------------------------------------
     sigma_u |  .18280987
     sigma_e |  .08356424
         rho |  .82716429   (fraction of variance due to u_i)
------------------------------------------------------------------------------
(est3 stored)

. drop Damaged_2019

. 
. esttab using "ax-tab_spillover_incumbent.tex", keep(Damaged_*)  replace b(%8.3f) se(%8.3f) noomitted nobaselev stats(N,  fmt(0 0))  star(+ 0.10 
> * 0.05 ** 0.01 *** 0.001)
(file ax-tab_spillover_incumbent.tex not found)
(output written to ax-tab_spillover_incumbent.tex)

. 
. ****************************************************************
. * Table of Pre-post DID Estimates Dropping Bolzano
. ****************************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22))
(56,441 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. keep if cod_reg != 3
(1,516 observations deleted)

. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. est clear

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_mean if anno == 2019
(161 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_mean if anno == 2009
(159 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_mean if anno == 2004
(157 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov if anno > 2009, fe cl(SLL)
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,068
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9756                                         min =          2
     Between = 0.2000                                         avg =        2.0
     Overall = 0.8820                                         max =          2

                                                F(6, 41)          =    1731.87
corr(u_i, Xb) = 0.0135                          Prob > F          =     0.0000

                               (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .2149928   .0906554     2.37   0.022     .0319105     .398075
              |
         anno |
        2019  |   .3462647   .0118772    29.15   0.000     .3222782    .3702513
              |
     cod_prov |
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 24  |   .0295537   .0133358     2.22   0.032     .0026215     .056486
     2019 25  |   .0190338   .0179488     1.06   0.295    -.0172145    .0552821
     2019 30  |   .0363152   .0140432     2.59   0.013     .0079545     .064676
     2019 93  |   .0289916   .0143046     2.03   0.049     .0001029    .0578804
              |
        _cons |   .1249513   .0023566    53.02   0.000      .120192    .1297106
--------------+----------------------------------------------------------------
      sigma_u |   .0612446
      sigma_e |  .04144151
          rho |  .68593551   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est1 stored)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9633                                         min =          2
     Between = 0.1478                                         avg =        4.0
     Overall = 0.8298                                         max =          4

                                                F(16, 41)         =    2590.15
corr(u_i, Xb) = 0.0165                          Prob > F          =     0.0000

                               (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |    .209393    .064037     3.27   0.002     .0800676    .3387183
              |
         anno |
        2009  |   .1026567   .0053524    19.18   0.000     .0918473    .1134661
        2014  |   .0105438   .0059402     1.77   0.083    -.0014528    .0225403
        2019  |   .3569184   .0090713    39.35   0.000     .3385986    .3752382
              |
     cod_prov |
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 24  |   .0676719   .0087515     7.73   0.000     .0499978     .085346
     2009 25  |   .0240162   .0086508     2.78   0.008     .0065455    .0414869
     2009 30  |  -.0081676   .0067768    -1.21   0.235    -.0218536    .0055183
     2009 93  |   .0118839   .0081674     1.46   0.153    -.0046106    .0283784
     2014 24  |  -.0158971    .008105    -1.96   0.057    -.0322654    .0004712
     2014 25  |  -.0558158   .0094246    -5.92   0.000    -.0748492   -.0367823
     2014 30  |  -.0059129   .0065343    -0.90   0.371    -.0191091    .0072833
     2014 93  |  -.0267539   .0068612    -3.90   0.000    -.0406103   -.0128975
     2019 24  |   .0135566   .0115325     1.18   0.247    -.0097337    .0368468
     2019 25  |  -.0368541   .0138881    -2.65   0.011    -.0649016   -.0088066
     2019 30  |      .0303   .0134684     2.25   0.030     .0031001    .0574998
     2019 93  |   .0021296    .012904     0.17   0.870    -.0239306    .0281897
              |
        _cons |   .1279547   .0017135    74.67   0.000     .1244942    .1314151
--------------+----------------------------------------------------------------
      sigma_u |  .06261334
      sigma_e |  .03424387
          rho |  .76975733   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est2 stored)

. eststo: xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9634                                         min =          2
     Between = 0.1661                                         avg =        4.0
     Overall = 0.8314                                         max =          4

                                                F(18, 41)         =    2302.76
corr(u_i, Xb) = 0.0186                          Prob > F          =     0.0000

                               (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .2149928   .0907879     2.37   0.023      .031643    .3983425
 Damaged_2009 |   .0951588   .0837494     1.14   0.262    -.0739765    .2642941
 Damaged_2004 |  -.0786486   .0784734    -1.00   0.322    -.2371288    .0798316
              |
         anno |
        2009  |   .0991883   .0058177    17.05   0.000     .0874391    .1109374
        2014  |   .0089575   .0064233     1.39   0.171    -.0040146    .0219297
        2019  |   .3552223   .0090026    39.46   0.000     .3370411    .3734034
              |
     cod_prov |
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 24  |   .0708261   .0088187     8.03   0.000     .0530164    .0886357
     2009 25  |   .0262761    .008421     3.12   0.003     .0092695    .0432828
     2009 30  |  -.0049362   .0071971    -0.69   0.497    -.0194711    .0095987
     2009 93  |   .0152993   .0084773     1.80   0.078     -.001821    .0324196
     2014 24  |  -.0144542   .0082106    -1.76   0.086    -.0310358    .0021274
     2014 25  |   -.054777   .0098439    -5.56   0.000    -.0746572   -.0348968
     2014 30  |  -.0044358   .0069246    -0.64   0.525    -.0184204    .0095488
     2014 93  |  -.0251916   .0072847    -3.46   0.001    -.0399034   -.0104798
     2019 24  |   .0150996   .0114291     1.32   0.194    -.0079821    .0381812
     2019 25  |  -.0357431   .0137324    -2.60   0.013    -.0634763     -.00801
     2019 30  |   .0318794   .0133114     2.39   0.021     .0049965    .0587624
     2019 93  |      .0038   .0128538     0.30   0.769    -.0221587    .0297587
              |
        _cons |   .1285963   .0019088    67.37   0.000     .1247415    .1324511
--------------+----------------------------------------------------------------
      sigma_u |  .06227214
      sigma_e |  .03422749
          rho |  .76798533   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est3 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_max if anno == 2019
(161 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_max if anno == 2009
(159 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_max if anno == 2004
(157 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov if anno > 2009, fe cl(SLL)
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,068
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9765                                         min =          2
     Between = 0.1794                                         avg =        2.0
     Overall = 0.8842                                         max =          2

                                                F(6, 41)          =    2610.64
corr(u_i, Xb) = 0.0146                          Prob > F          =     0.0000

                               (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0406666   .0090114     4.51   0.000     .0224677    .0588654
              |
         anno |
        2019  |    .327333   .0142493    22.97   0.000      .298556      .35611
              |
     cod_prov |
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 24  |   .0470781   .0150129     3.14   0.003     .0167589    .0773973
     2019 25  |   .0292983   .0160046     1.83   0.074    -.0030235    .0616202
     2019 30  |   .0543197   .0150785     3.60   0.001     .0238681    .0847713
     2019 93  |   .0451829   .0155759     2.90   0.006     .0137267     .076639
              |
        _cons |   .1249513   .0021673    57.65   0.000     .1205744    .1293282
--------------+----------------------------------------------------------------
      sigma_u |  .06079164
      sigma_e |  .04064524
          rho |  .69107321   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est4 stored)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9641                                         min =          2
     Between = 0.1512                                         avg =        4.0
     Overall = 0.8312                                         max =          4

                                                F(16, 41)         =    2643.61
corr(u_i, Xb) = 0.0172                          Prob > F          =     0.0000

                               (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0358261   .0072894     4.91   0.000     .0211047    .0505474
              |
         anno |
        2009  |   .1026546    .005351    19.18   0.000      .091848    .1134612
        2014  |   .0106378   .0059416     1.79   0.081    -.0013615    .0226371
        2019  |   .3407263   .0102686    33.18   0.000     .3199884    .3614642
              |
     cod_prov |
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 24  |   .0676703   .0087488     7.73   0.000     .0500018    .0853387
     2009 25  |   .0240183   .0086492     2.78   0.008     .0065509    .0414858
     2009 30  |  -.0081716   .0067762    -1.21   0.235    -.0218564    .0055131
     2009 93  |    .011886   .0081667     1.46   0.153     -.004607    .0283791
     2014 24  |  -.0160112    .008102    -1.98   0.055    -.0323734    .0003511
     2014 25  |  -.0560369   .0094582    -5.92   0.000    -.0751382   -.0369357
     2014 30  |   -.006016    .006536    -0.92   0.363    -.0192157    .0071836
     2014 93  |  -.0268479   .0068607    -3.91   0.000    -.0407034   -.0129925
     2019 24  |   .0285238   .0121526     2.35   0.024     .0039811    .0530664
     2019 25  |  -.0282903   .0128223    -2.21   0.033    -.0541854   -.0023952
     2019 30  |   .0456927   .0133373     3.43   0.001     .0187575     .072628
     2019 93  |   .0159135    .012542     1.27   0.212    -.0094155    .0412425
              |
        _cons |   .1279505   .0016828    76.03   0.000      .124552     .131349
--------------+----------------------------------------------------------------
      sigma_u |  .06248184
      sigma_e |  .03388337
          rho |  .77274977   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est5 stored)

. eststo: xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9642                                         min =          2
     Between = 0.1271                                         avg =        4.0
     Overall = 0.8295                                         max =          4

                                                F(18, 41)         =    2429.56
corr(u_i, Xb) = 0.0142                          Prob > F          =     0.0000

                               (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0406666   .0090246     4.51   0.000     .0224411     .058892
 Damaged_2009 |   .0102012   .0103321     0.99   0.329    -.0106649    .0310673
 Damaged_2004 |   .0044005    .006206     0.71   0.482    -.0081328    .0169337
              |
         anno |
        2009  |   .0993769   .0060846    16.33   0.000     .0870888    .1116651
        2014  |    .013133    .006543     2.01   0.051    -.0000809    .0263469
        2019  |    .340466   .0103429    32.92   0.000     .3195781     .361354
              |
     cod_prov |
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 24  |   .0706863    .008881     7.96   0.000     .0527508    .0886219
     2009 25  |   .0258045   .0082642     3.12   0.003     .0091147    .0424944
     2009 30  |  -.0050689   .0075306    -0.67   0.505    -.0202772    .0101394
     2009 93  |   .0147634   .0085756     1.72   0.093    -.0025554    .0320822
     2014 24  |  -.0183113   .0081756    -2.24   0.031    -.0348223   -.0018002
     2014 25  |  -.0574211   .0090631    -6.34   0.000    -.0757244   -.0391178
     2014 30  |  -.0083798   .0072712    -1.15   0.256    -.0230643    .0063046
     2014 93  |  -.0290395   .0078521    -3.70   0.001    -.0448971   -.0131819
     2019 24  |   .0287668   .0121466     2.37   0.023     .0042364    .0532973
     2019 25  |  -.0281228   .0127347    -2.21   0.033     -.053841   -.0024046
     2019 30  |   .0459399   .0132318     3.47   0.001     .0192178     .072662
     2019 93  |   .0161434   .0125915     1.28   0.207    -.0092856    .0415724
              |
        _cons |   .1269019   .0019919    63.71   0.000     .1228792    .1309247
--------------+----------------------------------------------------------------
      sigma_u |  .06289263
      sigma_e |  .03388082
          rho |  .77506922   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est6 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_binary if anno == 2019
(161 real changes made)

. gen Damaged_2009 = 0

. replace Damaged_2009 = damage_binary if anno == 2009
(159 real changes made)

. gen Damaged_2004 = 0

. replace Damaged_2004 = damage_binary if anno == 2004
(157 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov if anno > 2009, fe cl(SLL)
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      1,068
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9763                                         min =          2
     Between = 0.1792                                         avg =        2.0
     Overall = 0.8835                                         max =          2

                                                F(6, 41)          =    2239.07
corr(u_i, Xb) = 0.0141                          Prob > F          =     0.0000

                               (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0328522   .0077492     4.24   0.000     .0172024    .0485021
              |
         anno |
        2019  |   .3258903   .0146669    22.22   0.000     .2962698    .3555107
              |
     cod_prov |
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2019 24  |   .0488636   .0154617     3.16   0.003      .017638    .0800892
     2019 25  |   .0316986   .0168057     1.89   0.066    -.0022412    .0656384
     2019 30  |   .0559957   .0155351     3.60   0.001      .024622    .0873694
     2019 93  |   .0468034   .0159486     2.93   0.005     .0145945    .0790123
              |
        _cons |   .1249513   .0022231    56.21   0.000     .1204617    .1294408
--------------+----------------------------------------------------------------
      sigma_u |  .06095053
      sigma_e |  .04087135
          rho |  .68981759   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est7 stored)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9638                                         min =          2
     Between = 0.1499                                         avg =        4.0
     Overall = 0.8307                                         max =          4

                                                F(16, 41)         =    2497.76
corr(u_i, Xb) = 0.0169                          Prob > F          =     0.0000

                               (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0282621   .0067149     4.21   0.000      .014701    .0418232
              |
         anno |
        2009  |   .1026621   .0053545    19.17   0.000     .0918484    .1134758
        2014  |   .0106076   .0059436     1.78   0.082    -.0013958     .022611
        2019  |   .3399339   .0111906    30.38   0.000      .317334    .3625339
              |
     cod_prov |
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 24  |   .0676638   .0087513     7.73   0.000     .0499901    .0853374
     2009 25  |   .0240108   .0086517     2.78   0.008     .0065383    .0414833
     2009 30  |  -.0081774   .0067789    -1.21   0.235    -.0218676    .0055128
     2009 93  |   .0118785    .008169     1.45   0.154    -.0046191    .0283761
     2014 24  |  -.0159755   .0081043    -1.97   0.055    -.0323425    .0003916
     2014 25  |  -.0559892   .0094556    -5.92   0.000    -.0750851   -.0368933
     2014 30  |  -.0059832   .0065374    -0.92   0.365    -.0191857    .0072193
     2014 93  |  -.0268177   .0068628    -3.91   0.000    -.0406775    -.012958
     2019 24  |   .0296534   .0130263     2.28   0.028     .0033462    .0559605
     2019 25  |  -.0264475   .0136415    -1.94   0.059     -.053997     .001102
     2019 30  |   .0467134   .0141915     3.29   0.002     .0180532    .0753737
     2019 93  |   .0169169   .0132973     1.27   0.210    -.0099376    .0437714
              |
        _cons |   .1279528   .0017117    74.75   0.000      .124496    .1314096
--------------+----------------------------------------------------------------
      sigma_u |  .06253102
      sigma_e |  .03400528
          rho |  .77176315   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est8 stored)

. eststo: xtreg party_share Damaged_2019 Damaged_2009 Damaged_2004 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      2,113
Group variable: pro_com                         Number of groups  =        534

R-squared:                                      Obs per group:
     Within  = 0.9639                                         min =          2
     Between = 0.1002                                         avg =        4.0
     Overall = 0.8266                                         max =          4

                                                F(18, 41)         =    2390.53
corr(u_i, Xb) = 0.0105                          Prob > F          =     0.0000

                               (Std. err. adjusted for 42 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .0328522   .0077605     4.23   0.000     .0171795     .048525
 Damaged_2009 |   .0074556   .0090257     0.83   0.414    -.0107721    .0256833
 Damaged_2004 |   .0063908   .0057152     1.12   0.270    -.0051512    .0179328
              |
         anno |
        2009  |   .1018714   .0059538    17.11   0.000     .0898474    .1138954
        2014  |    .015383   .0065714     2.34   0.024     .0021118    .0286542
        2019  |   .3412733   .0109737    31.10   0.000     .3191115     .363435
              |
     cod_prov |
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
              |
anno#cod_prov |
     2009 24  |   .0684075   .0088737     7.71   0.000     .0504866    .0863283
     2009 25  |   .0244947   .0087201     2.81   0.008      .006884    .0421054
     2009 30  |  -.0074171   .0074129    -1.00   0.323    -.0223878    .0075536
     2009 93  |    .012584   .0083363     1.51   0.139    -.0042515    .0294195
     2014 24  |  -.0204647   .0081757    -2.50   0.016    -.0369759   -.0039535
     2014 25  |  -.0589449   .0085848    -6.87   0.000    -.0762821   -.0416076
     2014 30  |  -.0105653   .0073659    -1.43   0.159    -.0254409    .0043104
     2014 93  |  -.0310818   .0081724    -3.80   0.000    -.0475863   -.0145774
     2019 24  |   .0283989   .0128256     2.21   0.032     .0024971    .0543006
     2019 25  |  -.0272463   .0134022    -2.03   0.049    -.0543125   -.0001801
     2019 30  |   .0454304   .0139203     3.26   0.002     .0173179     .073543
     2019 93  |   .0157216   .0132226     1.19   0.241    -.0109821    .0424252
              |
        _cons |   .1260209   .0020792    60.61   0.000     .1218218    .1302201
--------------+----------------------------------------------------------------
      sigma_u |  .06347477
      sigma_e |  .03400953
          rho |  .77695407   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est9 stored)

. drop Damaged_2019 Damaged_2009 Damaged_2004

. 
. esttab using "ax-tab_results_without_Bolzano.tex", keep(Damaged_*)  replace b(%8.3f) se(%8.3f) noomitted nobaselev stats(N,  fmt(0 0))  star(+ 0
> .10 * 0.05 ** 0.01 *** 0.001)
(file ax-tab_results_without_Bolzano.tex not found)
(output written to ax-tab_results_without_Bolzano.tex)

. 
. ****************************************************************
. * Table of Pre-Post DID Estimates Including Moderately Affected Provinces (Lombardia)
. ****************************************************************
. 
. use "vaia.dta", clear
(Written by R.              )

. keep if tipo_elezione == "europea"
(2,536 observations deleted)

. keep if (party == "LN" & (cod_reg == 3 | cod_reg == 5 | cod_reg == 6 | cod_prov == 22))  | (party == "SVP" & cod_prov == 21)
(55,979 observations deleted)

. keep if damaged_prov_binary == 1 
(3,170 observations deleted)

. xtset pro_com anno

Panel variable: pro_com (unbalanced)
 Time variable: anno, 2004 to 2019, but with gaps
         Delta: 1 unit

. 
. est clear

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_fraction if anno == 2019
(279 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 14.cod_prov omitted because of collinearity
note: 16.cod_prov omitted because of collinearity
note: 17.cod_prov omitted because of collinearity
note: 21.cod_prov omitted because of collinearity
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity
note: 97.cod_prov omitted because of collinearity
note: 2009.anno#25.cod_prov omitted because of collinearity
note: 2014.anno#14.cod_prov omitted because of collinearity
note: 2019.anno#16.cod_prov omitted because of collinearity
note: 2019.anno#17.cod_prov omitted because of collinearity
note: 2019.anno#21.cod_prov omitted because of collinearity
note: 2019.anno#97.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      4,091
Group variable: pro_com                         Number of groups  =      1,408

R-squared:                                      Obs per group:
     Within  = 0.9628                                         min =          2
     Between = 0.1533                                         avg =        2.9
     Overall = 0.0899                                         max =          4

                                                F(24, 85)         =    7555.47
corr(u_i, Xb) = -0.5890                         Prob > F          =     0.0000

                               (Std. err. adjusted for 86 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |   .1035682    .048722     2.13   0.036     .0066958    .2004406
              |
         anno |
        2009  |   .1266729   .0068523    18.49   0.000     .1130487    .1402971
        2014  |  -.3690171   .0231442   -15.94   0.000    -.4150341   -.3230001
        2019  |  -.0186486   .0065678    -2.84   0.006    -.0317072     -.00559
              |
     cod_prov |
          14  |          0  (omitted)
          16  |          0  (omitted)
          17  |          0  (omitted)
          21  |          0  (omitted)
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
          97  |          0  (omitted)
              |
anno#cod_prov |
     2004 13  |          0  (empty)
     2004 14  |          0  (empty)
     2004 16  |          0  (empty)
     2004 17  |          0  (empty)
     2004 97  |          0  (empty)
     2009 13  |          0  (empty)
     2009 14  |          0  (empty)
     2009 16  |          0  (empty)
     2009 17  |          0  (empty)
     2009 21  |  -.0570471   .0086756    -6.58   0.000    -.0742965   -.0397977
     2009 22  |  -.0240105    .008591    -2.79   0.006    -.0410916   -.0069294
     2009 24  |   .0436561   .0097064     4.50   0.000     .0243572     .062955
     2009 25  |          0  (omitted)
     2009 30  |  -.0321828   .0078146    -4.12   0.000    -.0477203   -.0166452
     2009 93  |  -.0121323   .0091345    -1.33   0.188    -.0302941    .0060295
     2009 97  |          0  (empty)
     2014 14  |          0  (omitted)
     2014 16  |   .0183313   .0233006     0.79   0.434    -.0279965    .0646592
     2014 17  |   .0226434   .0237775     0.95   0.344    -.0246327    .0699195
     2014 21  |   .4016658    .022456    17.89   0.000     .3570172    .4463144
     2014 22  |   .3795736   .0239399    15.86   0.000     .3319746    .4271726
     2014 24  |   .3636661   .0237832    15.29   0.000     .3163787    .4109536
     2014 25  |   .3237519   .0240492    13.46   0.000     .2759356    .3715682
     2014 30  |   .3736496   .0233017    16.04   0.000     .3273195    .4199796
     2014 93  |    .352807   .0233939    15.08   0.000     .3062935    .3993204
     2014 97  |   .0421224   .0220946     1.91   0.060    -.0018076    .0860524
     2019 14  |  -.1429193   .0295819    -4.83   0.000     -.201736   -.0841025
     2019 16  |          0  (omitted)
     2019 17  |          0  (omitted)
     2019 21  |          0  (omitted)
     2019 22  |   .3764156   .0113055    33.29   0.000     .3539373    .3988939
     2019 24  |   .3892691   .0096939    40.16   0.000      .369995    .4085432
     2019 25  |   .3391199   .0122182    27.76   0.000     .3148268     .363413
     2019 30  |   .4060056   .0120532    33.68   0.000     .3820406    .4299707
     2019 93  |   .3777114   .0112086    33.70   0.000     .3554256    .3999971
     2019 97  |          0  (omitted)
              |
        _cons |   .3518445   .0035426    99.32   0.000      .344801    .3588881
--------------+----------------------------------------------------------------
      sigma_u |  .23701902
      sigma_e |  .03571139
          rho |  .97780279   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est1 stored)

. drop Damaged_2019

. 
. gen Damaged_2019 = 0

. replace Damaged_2019 = damage_binary if anno == 2019
(279 real changes made)

. eststo: xtreg party_share Damaged_2019 i.anno i.anno##i.cod_prov, fe cl(SLL)
note: 14.cod_prov omitted because of collinearity
note: 16.cod_prov omitted because of collinearity
note: 17.cod_prov omitted because of collinearity
note: 21.cod_prov omitted because of collinearity
note: 22.cod_prov omitted because of collinearity
note: 24.cod_prov omitted because of collinearity
note: 25.cod_prov omitted because of collinearity
note: 30.cod_prov omitted because of collinearity
note: 93.cod_prov omitted because of collinearity
note: 97.cod_prov omitted because of collinearity
note: 2009.anno#25.cod_prov omitted because of collinearity
note: 2014.anno#14.cod_prov omitted because of collinearity
note: 2019.anno#16.cod_prov omitted because of collinearity
note: 2019.anno#17.cod_prov omitted because of collinearity
note: 2019.anno#21.cod_prov omitted because of collinearity
note: 2019.anno#97.cod_prov omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =      4,091
Group variable: pro_com                         Number of groups  =      1,408

R-squared:                                      Obs per group:
     Within  = 0.9629                                         min =          2
     Between = 0.1533                                         avg =        2.9
     Overall = 0.0903                                         max =          4

                                                F(24, 85)         =    7383.52
corr(u_i, Xb) = -0.5881                         Prob > F          =     0.0000

                               (Std. err. adjusted for 86 clusters in SLL_2011)
-------------------------------------------------------------------------------
              |               Robust
  party_share | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
 Damaged_2019 |    .010819   .0063821     1.70   0.094    -.0018704    .0235083
              |
         anno |
        2009  |   .1266729   .0068523    18.49   0.000     .1130487    .1402971
        2014  |  -.3689983   .0231534   -15.94   0.000    -.4150334   -.3229633
        2019  |  -.0190496   .0065754    -2.90   0.005    -.0321233   -.0059759
              |
     cod_prov |
          14  |          0  (omitted)
          16  |          0  (omitted)
          17  |          0  (omitted)
          21  |          0  (omitted)
          22  |          0  (omitted)
          24  |          0  (omitted)
          25  |          0  (omitted)
          30  |          0  (omitted)
          93  |          0  (omitted)
          97  |          0  (omitted)
              |
anno#cod_prov |
     2004 13  |          0  (empty)
     2004 14  |          0  (empty)
     2004 16  |          0  (empty)
     2004 17  |          0  (empty)
     2004 97  |          0  (empty)
     2009 13  |          0  (empty)
     2009 14  |          0  (empty)
     2009 16  |          0  (empty)
     2009 17  |          0  (empty)
     2009 21  |   -.057019   .0086688    -6.58   0.000    -.0742549   -.0397831
     2009 22  |  -.0240027   .0085924    -2.79   0.006    -.0410866   -.0069187
     2009 24  |   .0436553   .0097062     4.50   0.000     .0243569    .0629538
     2009 25  |          0  (omitted)
     2009 30  |  -.0321842   .0078148    -4.12   0.000     -.047722   -.0166463
     2009 93  |  -.0121323   .0091345    -1.33   0.188    -.0302941    .0060295
     2009 97  |          0  (empty)
     2014 14  |          0  (omitted)
     2014 16  |   .0185632   .0232209     0.80   0.426    -.0276061    .0647325
     2014 17  |    .025224   .0238296     1.06   0.293    -.0221557    .0726037
     2014 21  |   .4016751   .0224525    17.89   0.000     .3570336    .4463166
     2014 22  |   .3795887   .0239532    15.85   0.000     .3319632    .4272142
     2014 24  |   .3636432   .0237913    15.28   0.000     .3163398    .4109466
     2014 25  |   .3236991     .02406    13.45   0.000     .2758613    .3715369
     2014 30  |   .3736287   .0233105    16.03   0.000     .3272812    .4199762
     2014 93  |   .3527882   .0234028    15.07   0.000     .3062571    .3993193
     2014 97  |   .0418285   .0220802     1.89   0.062    -.0020729    .0857299
     2019 14  |  -.1464758   .0301251    -4.86   0.000    -.2063725   -.0865791
     2019 16  |          0  (omitted)
     2019 17  |          0  (omitted)
     2019 21  |          0  (omitted)
     2019 22  |   .3720237   .0125353    29.68   0.000     .3471003    .3969472
     2019 24  |   .3894147   .0096459    40.37   0.000      .370236    .4085934
     2019 25  |   .3374797   .0116672    28.93   0.000      .314282    .3606773
     2019 30  |   .4062237   .0119587    33.97   0.000     .3824466    .4300007
     2019 93  |   .3772958   .0108552    34.76   0.000     .3557129    .3988788
     2019 97  |          0  (omitted)
              |
        _cons |   .3515594   .0035602    98.75   0.000     .3444809     .358638
--------------+----------------------------------------------------------------
      sigma_u |  .23673205
      sigma_e |  .03568197
          rho |  .97778598   (fraction of variance due to u_i)
-------------------------------------------------------------------------------
(est2 stored)

. drop Damaged_2019

. 
. esttab using "ax-tab_did_lombardia.tex", keep(Damaged_*)  replace b(%8.3f) se(%8.3f) noomitted nobaselev stats(N,  fmt(0 0))  star(+ 0.10 * 0.05
>  ** 0.01 *** 0.001)
(file ax-tab_did_lombardia.tex not found)
(output written to ax-tab_did_lombardia.tex)

. 
. 
end of do-file

. 
. log close
      name:  <unnamed>
       log:  C:\Users\smncr\OneDrive - Università Commerciale Luigi Bocconi\VAIA\JOP Dataverse\Dataverse\Stata_log.log
  log type:  text
 closed on:   6 Jun 2024, 09:43:02
--------------------------------------------------------------------------------------------------------------------------------------------------
